Pandas Profiling Report

Dataset statistics

Number of variables	24
Number of observations	4803
Missing cells	4454
Missing cells (%)	3.9%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	900.7 KiB
Average record size in memory	192.0 B

Variable types

Numeric	8
Categorical	16

Alerts

`genres` has a high cardinality: 1168 distinct values	High cardinality
`homepage` has a high cardinality: 1691 distinct values	High cardinality
`keywords` has a high cardinality: 4219 distinct values	High cardinality
`original_title` has a high cardinality: 4801 distinct values	High cardinality
`overview` has a high cardinality: 4800 distinct values	High cardinality
`production_companies` has a high cardinality: 3697 distinct values	High cardinality
`production_countries` has a high cardinality: 469 distinct values	High cardinality
`release_date` has a high cardinality: 3280 distinct values	High cardinality
`spoken_languages` has a high cardinality: 544 distinct values	High cardinality
`tagline` has a high cardinality: 3944 distinct values	High cardinality
`title` has a high cardinality: 4800 distinct values	High cardinality
`cast` has a high cardinality: 4741 distinct values	High cardinality
`crew` has a high cardinality: 4776 distinct values	High cardinality
`director` has a high cardinality: 2349 distinct values	High cardinality
`df_index` is highly overall correlated with `budget` and 3 other fields	High correlation
`budget` is highly overall correlated with `df_index` and 3 other fields	High correlation
`popularity` is highly overall correlated with `df_index` and 3 other fields	High correlation
`revenue` is highly overall correlated with `df_index` and 3 other fields	High correlation
`vote_count` is highly overall correlated with `df_index` and 3 other fields	High correlation
`original_language` is highly imbalanced (88.8%)	Imbalance
`production_countries` is highly imbalanced (60.9%)	Imbalance
`spoken_languages` is highly imbalanced (62.6%)	Imbalance
`status` is highly imbalanced (98.8%)	Imbalance
`homepage` has 3091 (64.4%) missing values	Missing
`keywords` has 412 (8.6%) missing values	Missing
`tagline` has 844 (17.6%) missing values	Missing
`df_index` is uniformly distributed	Uniform
`homepage` is uniformly distributed	Uniform
`original_title` is uniformly distributed	Uniform
`overview` is uniformly distributed	Uniform
`release_date` is uniformly distributed	Uniform
`tagline` is uniformly distributed	Uniform
`title` is uniformly distributed	Uniform
`cast` is uniformly distributed	Uniform
`crew` is uniformly distributed	Uniform
`df_index` has unique values	Unique
`id` has unique values	Unique
`budget` has 1037 (21.6%) zeros	Zeros
`revenue` has 1427 (29.7%) zeros	Zeros
`vote_average` has 63 (1.3%) zeros	Zeros
`vote_count` has 62 (1.3%) zeros	Zeros

Reproduction

Analysis started	2023-08-04 12:54:59.970891
Analysis finished	2023-08-04 12:55:10.202909
Duration	10.23 seconds
Software version	pandas-profiling v3.6.6
Download configuration	config.json

df_index
Real number (ℝ)

HIGH CORRELATION UNIFORM UNIQUE

Distinct	4803
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2401

Minimum	0
Maximum	4802
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	37.6 KiB

Quantile statistics

Minimum	0
5-th percentile	240.1
Q1	1200.5
median	2401
Q3	3601.5
95-th percentile	4561.9
Maximum	4802
Range	4802
Interquartile range (IQR)	2401

Descriptive statistics

Standard deviation	1386.651
Coefficient of variation (CV)	0.57753061
Kurtosis	-1.2
Mean	2401
Median Absolute Deviation (MAD)	1201
Skewness	0
Sum	11532003
Variance	1922801
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1	< 0.1%
3208	1	< 0.1%
3206	1	< 0.1%
3205	1	< 0.1%
3204	1	< 0.1%
3203	1	< 0.1%
3202	1	< 0.1%
3201	1	< 0.1%
3200	1	< 0.1%
3199	1	< 0.1%
Other values (4793)	4793	99.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
4802	1	< 0.1%
4801	1	< 0.1%
4800	1	< 0.1%
4799	1	< 0.1%
4798	1	< 0.1%
4797	1	< 0.1%
4796	1	< 0.1%
4795	1	< 0.1%
4794	1	< 0.1%
4793	1	< 0.1%

budget
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	436
Distinct (%)	9.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	29045040

Minimum	0
Maximum	3.8 × 10⁸
Zeros	1037
Zeros (%)	21.6%
Negative	0
Negative (%)	0.0%
Memory size	37.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	790000
median	15000000
Q3	40000000
95-th percentile	1.15 × 10⁸
Maximum	3.8 × 10⁸
Range	3.8 × 10⁸
Interquartile range (IQR)	39210000

Descriptive statistics

Standard deviation	40722391
Coefficient of variation (CV)	1.4020429
Kurtosis	7.6580602
Mean	29045040
Median Absolute Deviation (MAD)	15000000
Skewness	2.437211
Sum	1.3950333 × 10¹¹
Variance	1.6583131 × 10¹⁵
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1037	21.6%
20000000	144	3.0%
30000000	128	2.7%
25000000	126	2.6%
40000000	123	2.6%
15000000	120	2.5%
35000000	102	2.1%
50000000	101	2.1%
10000000	101	2.1%
60000000	86	1.8%
Other values (426)	2735	56.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1037	21.6%
1	7	0.1%
2	1	< 0.1%
3	1	< 0.1%
4	2	< 0.1%
7	2	< 0.1%
8	1	< 0.1%
10	3	0.1%
11	1	< 0.1%
13	1	< 0.1%

Value	Count	Frequency (%)
380000000	1	< 0.1%
300000000	1	< 0.1%
280000000	1	< 0.1%
270000000	1	< 0.1%
260000000	2	< 0.1%
258000000	1	< 0.1%
255000000	1	< 0.1%
250000000	8	0.2%
245000000	1	< 0.1%
237000000	1	< 0.1%

genres
Categorical

Distinct	1168
Distinct (%)	24.5%
Missing	28
Missing (%)	0.6%
Memory size	37.6 KiB

Drama	370
Comedy	282
Drama Romance	164
Comedy Romance	144
Comedy Drama	142
Other values (1163)	3673

Length

Max length	51
Median length	44
Mean length	18.711623
Min length	3

Characters and Unicode

Total characters	89348
Distinct characters	29
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	731 ?
Unique (%)	15.3%

Sample

1st row	Action Adventure Fantasy Science Fiction
2nd row	Adventure Fantasy Action
3rd row	Action Adventure Crime
4th row	Action Crime Drama Thriller
5th row	Action Adventure Science Fiction

Common Values

Value	Count	Frequency (%)
Drama	370	7.7%
Comedy	282	5.9%
Drama Romance	164	3.4%
Comedy Romance	144	3.0%
Comedy Drama	142	3.0%
Comedy Drama Romance	109	2.3%
Horror Thriller	88	1.8%
Documentary	68	1.4%
Horror	64	1.3%
Drama Thriller	62	1.3%
Other values (1158)	3282	68.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
drama	2297	18.1%
comedy	1722	13.6%
thriller	1259	9.9%
action	1153	9.1%
romance	890	7.0%
adventure	790	6.2%
crime	696	5.5%
fiction	530	4.2%
science	530	4.2%
horror	519	4.1%
Other values (12)	2271	17.9%

Most occurring characters

Value	Count	Frequency (%)
r	8768	9.8%
	7882	8.8%
e	7866	8.8%
a	7316	8.2%
m	6459	7.2%
i	6098	6.8%
o	5916	6.6%
n	5003	5.6%
c	3926	4.4%
t	3859	4.3%
Other values (19)	26255	29.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	68801	77.0%
Uppercase Letter	12665	14.2%
Space Separator	7882	8.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	8768	12.7%
e	7866	11.4%
a	7316	10.6%
m	6459	9.4%
i	6098	8.9%
o	5916	8.6%
n	5003	7.3%
c	3926	5.7%
t	3859	5.6%
y	3651	5.3%
Other values (7)	9939	14.4%

Uppercase Letter

Value	Count	Frequency (%)
C	2418	19.1%
D	2407	19.0%
A	2177	17.2%
F	1492	11.8%
T	1267	10.0%
R	890	7.0%
H	716	5.7%
M	538	4.2%
S	530	4.2%
W	222	1.8%

Space Separator

Value	Count	Frequency (%)
	7882	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	81466	91.2%
Common	7882	8.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	8768	10.8%
e	7866	9.7%
a	7316	9.0%
m	6459	7.9%
i	6098	7.5%
o	5916	7.3%
n	5003	6.1%
c	3926	4.8%
t	3859	4.7%
y	3651	4.5%
Other values (18)	22604	27.7%

Common

Value	Count	Frequency (%)
	7882	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	89348	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
r	8768	9.8%
	7882	8.8%
e	7866	8.8%
a	7316	8.2%
m	6459	7.2%
i	6098	6.8%
o	5916	6.6%
n	5003	5.6%
c	3926	4.4%
t	3859	4.3%
Other values (19)	26255	29.4%

homepage
Categorical

HIGH CARDINALITY MISSING UNIFORM

Distinct	1691
Distinct (%)	98.8%
Missing	3091
Missing (%)	64.4%
Memory size	37.6 KiB

http://www.missionimpossible.com/	4
http://www.thehungergames.movie/	4
http://www.transformersmovie.com/	3
http://www.thehobbit.com/	3
http://www.kungfupanda.com/	3
Other values (1686)	1695

Length

Max length	138
Median length	80
Mean length	36.419977
Min length	17

Characters and Unicode

Total characters	62351
Distinct characters	78
Distinct categories	10 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1677 ?
Unique (%)	98.0%

Sample

1st row	http://www.avatarmovie.com/
2nd row	http://disney.go.com/disneypictures/pirates/
3rd row	http://www.sonypictures.com/movies/spectre/
4th row	http://www.thedarkknightrises.com/
5th row	http://movies.disney.com/john-carter

Common Values

Value	Count	Frequency (%)
http://www.missionimpossible.com/	4	0.1%
http://www.thehungergames.movie/	4	0.1%
http://www.transformersmovie.com/	3	0.1%
http://www.thehobbit.com/	3	0.1%
http://www.kungfupanda.com/	3	0.1%
http://www.munkyourself.com/	2	< 0.1%
http://www.lordoftherings.net/	2	< 0.1%
http://www.workandtheglory.com/	2	< 0.1%
http://www.theamazingspiderman.com	2	< 0.1%
http://www.indianajones.com	2	< 0.1%
Other values (1681)	1685	35.1%
(Missing)	3091	64.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
http://www.missionimpossible.com	5	0.3%
http://www.transformersmovie.com	4	0.2%
http://www.thehungergames.movie	4	0.2%
http://www.thehobbit.com	3	0.2%
http://www.kungfupanda.com	3	0.2%
http://www.lordoftherings.net	3	0.2%
http://disney.go.com/disneypictures/pirates	2	0.1%
http://www.teenagemutantninjaturtlesmovie.com	2	0.1%
http://www.atlasshruggedmovie.com	2	0.1%
http://www.twilightthemovie.com	2	0.1%
Other values (1675)	1683	98.2%

Most occurring characters

Value	Count	Frequency (%)
t	5707	9.2%
/	5701	9.1%
e	4467	7.2%
o	4438	7.1%
w	4418	7.1%
m	3492	5.6%
.	3393	5.4%
h	3110	5.0%
i	3017	4.8%
c	2543	4.1%
Other values (68)	22065	35.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	49986	80.2%
Other Punctuation	10851	17.4%
Dash Punctuation	613	1.0%
Decimal Number	557	0.9%
Uppercase Letter	245	0.4%
Connector Punctuation	68	0.1%
Math Symbol	22	< 0.1%
Close Punctuation	4	< 0.1%
Open Punctuation	4	< 0.1%
Space Separator	1	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
t	5707	11.4%
e	4467	8.9%
o	4438	8.9%
w	4418	8.8%
m	3492	7.0%
h	3110	6.2%
i	3017	6.0%
c	2543	5.1%
p	2347	4.7%
s	2280	4.6%
Other values (16)	14167	28.3%

Uppercase Letter

Value	Count	Frequency (%)
D	22	9.0%
T	20	8.2%
A	20	8.2%
M	19	7.8%
S	17	6.9%
E	14	5.7%
L	13	5.3%
G	12	4.9%
H	10	4.1%
W	10	4.1%
Other values (15)	88	35.9%

Decimal Number

Value	Count	Frequency (%)
2	104	18.7%
1	87	15.6%
0	84	15.1%
3	71	12.7%
9	44	7.9%
5	35	6.3%
4	34	6.1%
7	33	5.9%
6	33	5.9%
8	32	5.7%

Other Punctuation

Value	Count	Frequency (%)
/	5701	52.5%
.	3393	31.3%
:	1713	15.8%
#	18	0.2%
?	18	0.2%
&	3	< 0.1%
%	3	< 0.1%
,	1	< 0.1%
!	1	< 0.1%

Close Punctuation

Value	Count	Frequency (%)
)	3	75.0%
}	1	25.0%

Open Punctuation

Value	Count	Frequency (%)
(	3	75.0%
{	1	25.0%

Dash Punctuation

Value	Count	Frequency (%)
-	613	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	68	100.0%

Math Symbol

Value	Count	Frequency (%)
=	22	100.0%

Space Separator

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	50231	80.6%
Common	12120	19.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
t	5707	11.4%
e	4467	8.9%
o	4438	8.8%
w	4418	8.8%
m	3492	7.0%
h	3110	6.2%
i	3017	6.0%
c	2543	5.1%
p	2347	4.7%
s	2280	4.5%
Other values (41)	14412	28.7%

Common

Value	Count	Frequency (%)
/	5701	47.0%
.	3393	28.0%
:	1713	14.1%
-	613	5.1%
2	104	0.9%
1	87	0.7%
0	84	0.7%
3	71	0.6%
_	68	0.6%
9	44	0.4%
Other values (17)	242	2.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	62351	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
t	5707	9.2%
/	5701	9.1%
e	4467	7.2%
o	4438	7.1%
w	4418	7.1%
m	3492	5.6%
.	3393	5.4%
h	3110	5.0%
i	3017	4.8%
c	2543	4.1%
Other values (68)	22065	35.4%

id
Real number (ℝ)

Distinct	4803
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	57165.484

Minimum	5
Maximum	459488
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	37.6 KiB

Quantile statistics

Minimum	5
5-th percentile	578.1
Q1	9014.5
median	14629
Q3	58610.5
95-th percentile	285779
Maximum	459488
Range	459483
Interquartile range (IQR)	49596

Descriptive statistics

Standard deviation	88694.614
Coefficient of variation (CV)	1.5515414
Kurtosis	3.3467477
Mean	57165.484
Median Absolute Deviation (MAD)	12920
Skewness	2.0720805
Sum	2.7456582 × 10⁸
Variance	7.8667346 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
19995	1	< 0.1%
333355	1	< 0.1%
71157	1	< 0.1%
43418	1	< 0.1%
11588	1	< 0.1%
52010	1	< 0.1%
9671	1	< 0.1%
25968	1	< 0.1%
41248	1	< 0.1%
291081	1	< 0.1%
Other values (4793)	4793	99.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
5	1	< 0.1%
11	1	< 0.1%
12	1	< 0.1%
13	1	< 0.1%
14	1	< 0.1%
16	1	< 0.1%
18	1	< 0.1%
19	1	< 0.1%
20	1	< 0.1%
22	1	< 0.1%

Value	Count	Frequency (%)
459488	1	< 0.1%
447027	1	< 0.1%
433715	1	< 0.1%
426469	1	< 0.1%
426067	1	< 0.1%
417859	1	< 0.1%
408429	1	< 0.1%
407887	1	< 0.1%
402515	1	< 0.1%
396152	1	< 0.1%

keywords
Categorical

HIGH CARDINALITY MISSING

Distinct	4219
Distinct (%)	96.1%
Missing	412
Missing (%)	8.6%
Memory size	37.6 KiB

independent film	55
woman director	42
duringcreditsstinger	15
sport	13
independent film woman director	10
Other values (4214)	4256

Length

Max length	129
Median length	84
Mean length	45.549761
Min length	2

Characters and Unicode

Total characters	200009
Distinct characters	46
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4188 ?
Unique (%)	95.4%

Sample

1st row	culture clash future space war space colony society
2nd row	ocean drug abuse exotic island east india trading company love of one's life
3rd row	spy based on novel secret agent sequel mi6
4th row	dc comics crime fighter terrorist secret identity burglar
5th row	based on novel mars medallion space travel princess

Common Values

Value	Count	Frequency (%)
independent film	55	1.1%
woman director	42	0.9%
duringcreditsstinger	15	0.3%
sport	13	0.3%
independent film woman director	10	0.2%
biography	5	0.1%
suspense	5	0.1%
musical	5	0.1%
dystopia	3	0.1%
christian	3	0.1%
Other values (4209)	4235	88.2%
(Missing)	412	8.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
relationship	337	1.2%
of	336	1.2%
on	331	1.2%
based	303	1.1%
film	276	1.0%
independent	223	0.8%
love	206	0.7%
novel	206	0.7%
war	198	0.7%
new	194	0.7%
Other values (4377)	25186	90.6%

Most occurring characters

Value	Count	Frequency (%)
	23422	11.7%
e	18901	9.5%
i	15300	7.6%
a	14941	7.5%
r	14107	7.1%
n	12766	6.4%
o	12572	6.3%
t	11792	5.9%
s	11622	5.8%
l	8826	4.4%
Other values (36)	55760	27.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	175665	87.8%
Space Separator	23422	11.7%
Decimal Number	402	0.2%
Dash Punctuation	245	0.1%
Other Punctuation	243	0.1%
Close Punctuation	16	< 0.1%
Open Punctuation	16	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	18901	10.8%
i	15300	8.7%
a	14941	8.5%
r	14107	8.0%
n	12766	7.3%
o	12572	7.2%
t	11792	6.7%
s	11622	6.6%
l	8826	5.0%
c	6962	4.0%
Other values (16)	47876	27.3%

Decimal Number

Value	Count	Frequency (%)
0	113	28.1%
9	70	17.4%
1	70	17.4%
7	47	11.7%
3	42	10.4%
5	16	4.0%
6	15	3.7%
8	15	3.7%
2	11	2.7%
4	3	0.7%

Other Punctuation

Value	Count	Frequency (%)
.	100	41.2%
'	94	38.7%
\	43	17.7%
,	3	1.2%
"	2	0.8%
&	1	0.4%

Space Separator

Value	Count	Frequency (%)
	23422	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	245	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	16	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	16	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	175665	87.8%
Common	24344	12.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	18901	10.8%
i	15300	8.7%
a	14941	8.5%
r	14107	8.0%
n	12766	7.3%
o	12572	7.2%
t	11792	6.7%
s	11622	6.6%
l	8826	5.0%
c	6962	4.0%
Other values (16)	47876	27.3%

Common

Value	Count	Frequency (%)
	23422	96.2%
-	245	1.0%
0	113	0.5%
.	100	0.4%
'	94	0.4%
9	70	0.3%
1	70	0.3%
7	47	0.2%
\	43	0.2%
3	42	0.2%
Other values (10)	98	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	200009	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	23422	11.7%
e	18901	9.5%
i	15300	7.6%
a	14941	7.5%
r	14107	7.1%
n	12766	6.4%
o	12572	6.3%
t	11792	5.9%
s	11622	5.8%
l	8826	4.4%
Other values (36)	55760	27.9%

original_language
Categorical

Distinct	37
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Memory size	37.6 KiB

en	4505
fr	70
es	32
zh	27
de	27
Other values (32)	142

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	9606
Distinct characters	22
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	14 ?
Unique (%)	0.3%

Sample

1st row	en
2nd row	en
3rd row	en
4th row	en
5th row	en

Common Values

Value	Count	Frequency (%)
en	4505	93.8%
fr	70	1.5%
es	32	0.7%
zh	27	0.6%
de	27	0.6%
hi	19	0.4%
ja	16	0.3%
it	14	0.3%
cn	12	0.2%
ru	11	0.2%
Other values (27)	70	1.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
en	4505	93.8%
fr	70	1.5%
es	32	0.7%
zh	27	0.6%
de	27	0.6%
hi	19	0.4%
ja	16	0.3%
it	14	0.3%
cn	12	0.2%
ko	11	0.2%
Other values (27)	70	1.5%

Most occurring characters

Value	Count	Frequency (%)
e	4569	47.6%
n	4523	47.1%
r	86	0.9%
f	75	0.8%
h	53	0.6%
s	42	0.4%
i	37	0.4%
d	36	0.4%
a	32	0.3%
t	30	0.3%
Other values (12)	123	1.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	9606	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	4569	47.6%
n	4523	47.1%
r	86	0.9%
f	75	0.8%
h	53	0.6%
s	42	0.4%
i	37	0.4%
d	36	0.4%
a	32	0.3%
t	30	0.3%
Other values (12)	123	1.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	9606	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	4569	47.6%
n	4523	47.1%
r	86	0.9%
f	75	0.8%
h	53	0.6%
s	42	0.4%
i	37	0.4%
d	36	0.4%
a	32	0.3%
t	30	0.3%
Other values (12)	123	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	9606	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	4569	47.6%
n	4523	47.1%
r	86	0.9%
f	75	0.8%
h	53	0.6%
s	42	0.4%
i	37	0.4%
d	36	0.4%
a	32	0.3%
t	30	0.3%
Other values (12)	123	1.3%

original_title
Categorical

HIGH CARDINALITY UNIFORM

Distinct	4801
Distinct (%)	> 99.9%
Missing	0
Missing (%)	0.0%
Memory size	37.6 KiB

Out of the Blue	2
Batman	2
Undiscovered	1
Beneath Hill 60	1
The I Inside	1
Other values (4796)	4796

Length

Max length	86
Median length	59
Mean length	15.222986
Min length	1

Characters and Unicode

Total characters	73116
Distinct characters	410
Distinct categories	19 ?
Distinct scripts	13 ?
Distinct blocks	14 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4799 ?
Unique (%)	99.9%

Sample

1st row	Avatar
2nd row	Pirates of the Caribbean: At World's End
3rd row	Spectre
4th row	The Dark Knight Rises
5th row	John Carter

Common Values

Value	Count	Frequency (%)
Out of the Blue	2	< 0.1%
Batman	2	< 0.1%
Undiscovered	1	< 0.1%
Beneath Hill 60	1	< 0.1%
The I Inside	1	< 0.1%
Ultramarines: A Warhammer 40,000 Movie	1	< 0.1%
Crocodile Dundee	1	< 0.1%
Veronika Decides to Die	1	< 0.1%
La Fille du RER	1	< 0.1%
Red Riding: In the Year of Our Lord 1974	1	< 0.1%
Other values (4791)	4791	99.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
the	1420	10.7%
of	432	3.3%
a	168	1.3%
and	127	1.0%
in	110	0.8%
2	102	0.8%
to	102	0.8%
	80	0.6%
man	65	0.5%
love	53	0.4%
Other values (5055)	10578	79.9%

Most occurring characters

Value	Count	Frequency (%)
	8436	11.5%
e	7412	10.1%
a	4625	6.3%
o	4370	6.0%
r	3892	5.3%
n	3885	5.3%
i	3723	5.1%
t	3600	4.9%
s	2857	3.9%
h	2717	3.7%
Other values (400)	27599	37.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	51401	70.3%
Uppercase Letter	11413	15.6%
Space Separator	8436	11.5%
Other Punctuation	906	1.2%
Decimal Number	494	0.7%
Other Letter	328	0.4%
Dash Punctuation	84	0.1%
Spacing Mark	16	< 0.1%
Nonspacing Mark	8	< 0.1%
Close Punctuation	6	< 0.1%
Other values (9)	24	< 0.1%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
ا	7	2.1%
の	7	2.1%
ی	6	1.8%
三	5	1.5%
的	4	1.2%
城	4	1.2%
क	4	1.2%
ن	4	1.2%
十	3	0.9%
د	3	0.9%
Other values (229)	281	85.7%

Lowercase Letter

Value	Count	Frequency (%)
e	7412	14.4%
a	4625	9.0%
o	4370	8.5%
r	3892	7.6%
n	3885	7.6%
i	3723	7.2%
t	3600	7.0%
s	2857	5.6%
h	2717	5.3%
l	2426	4.7%
Other values (70)	11894	23.1%

Uppercase Letter

Value	Count	Frequency (%)
T	1562	13.7%
S	972	8.5%
M	777	6.8%
B	733	6.4%
D	680	6.0%
C	638	5.6%
A	618	5.4%
L	565	5.0%
H	526	4.6%
P	470	4.1%
Other values (27)	3872	33.9%

Other Punctuation

Value	Count	Frequency (%)
:	341	37.6%
'	222	24.5%
.	141	15.6%
,	75	8.3%
&	60	6.6%
!	35	3.9%
?	18	2.0%
/	7	0.8%
#	2	0.2%
*	2	0.2%
Other values (3)	3	0.3%

Decimal Number

Value	Count	Frequency (%)
2	144	29.1%
1	78	15.8%
3	74	15.0%
0	74	15.0%
4	35	7.1%
5	21	4.3%
8	21	4.3%
9	17	3.4%
7	15	3.0%
6	15	3.0%

Spacing Mark

Value	Count	Frequency (%)
ी	5	31.2%
ா	3	18.8%
ा	3	18.8%
ு	2	12.5%
ि	2	12.5%
ो	1	6.2%

Nonspacing Mark

Value	Count	Frequency (%)
ุ	2	25.0%
้	2	25.0%
்	1	12.5%
ृ	1	12.5%
ิ	1	12.5%
े	1	12.5%

Other Number

Value	Count	Frequency (%)
³	1	25.0%
½	1	25.0%
²	1	25.0%
⅓	1	25.0%

Dash Punctuation

Value	Count	Frequency (%)
-	82	97.6%
–	2	2.4%

Close Punctuation

Value	Count	Frequency (%)
)	4	66.7%
]	2	33.3%

Open Punctuation

Value	Count	Frequency (%)
(	4	66.7%
[	2	33.3%

Currency Symbol

Value	Count	Frequency (%)
$	3	60.0%
¢	2	40.0%

Space Separator

Value	Count	Frequency (%)
	8436	100.0%

Final Punctuation

Value	Count	Frequency (%)
’	3	100.0%

Math Symbol

Value	Count	Frequency (%)
+	2	100.0%

Modifier Letter

Value	Count	Frequency (%)
ー	1	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	1	100.0%

Format

Value	Count	Frequency (%)
‌	1	100.0%

Other Symbol

Value	Count	Frequency (%)
°	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	62677	85.7%
Common	9949	13.6%
Han	160	0.2%
Cyrillic	127	0.2%
Hangul	45	0.1%
Arabic	39	0.1%
Devanagari	35	< 0.1%
Katakana	26	< 0.1%
Hiragana	17	< 0.1%
Thai	17	< 0.1%
Other values (3)	24	< 0.1%

Most frequent character per script

Han

Value	Count	Frequency (%)
三	5	3.1%
的	4	2.5%
城	4	2.5%
十	3	1.9%
一	3	1.9%
人	3	1.9%
暴	2	1.2%
七	2	1.2%
之	2	1.2%
石	2	1.2%
Other values (113)	130	81.2%

Latin

Value	Count	Frequency (%)
e	7412	11.8%
a	4625	7.4%
o	4370	7.0%
r	3892	6.2%
n	3885	6.2%
i	3723	5.9%
t	3600	5.7%
s	2857	4.6%
h	2717	4.3%
l	2426	3.9%
Other values (62)	23170	37.0%

Common

Value	Count	Frequency (%)
	8436	84.8%
:	341	3.4%
'	222	2.2%
2	144	1.4%
.	141	1.4%
-	82	0.8%
1	78	0.8%
,	75	0.8%
3	74	0.7%
0	74	0.7%
Other values (31)	282	2.8%

Hangul

Value	Count	Frequency (%)
놈	3	6.7%
이	2	4.4%
상	2	4.4%
한	2	4.4%
금	1	2.2%
자	1	2.2%
씨	1	2.2%
실	1	2.2%
올	1	2.2%
드	1	2.2%
Other values (30)	30	66.7%

Cyrillic

Value	Count	Frequency (%)
о	18	14.2%
е	10	7.9%
а	10	7.9%
р	9	7.1%
н	8	6.3%
л	7	5.5%
в	6	4.7%
и	6	4.7%
С	5	3.9%
б	4	3.1%
Other values (26)	44	34.6%

Devanagari

Value	Count	Frequency (%)
ी	5	14.3%
क	4	11.4%
ा	3	8.6%
भ	2	5.7%
ह	2	5.7%
ि	2	5.7%
ल	2	5.7%
न	2	5.7%
द	2	5.7%
ए	1	2.9%
Other values (10)	10	28.6%

Katakana

Value	Count	Frequency (%)
キ	3	11.5%
ア	2	7.7%
ラ	2	7.7%
ハ	2	7.7%
ン	2	7.7%
ゴ	1	3.8%
シ	1	3.8%
ジ	1	3.8%
ポ	1	3.8%
ニ	1	3.8%
Other values (10)	10	38.5%

Arabic

Value	Count	Frequency (%)
ا	7	17.9%
ی	6	15.4%
ن	4	10.3%
د	3	7.7%
ر	3	7.7%
س	3	7.7%
ه	3	7.7%
م	2	5.1%
ب	2	5.1%
آ	1	2.6%
Other values (5)	5	12.8%

Thai

Value	Count	Frequency (%)
ย	2	11.8%
ุ	2	11.8%
้	2	11.8%
ก	1	5.9%
ำ	1	5.9%
ม	1	5.9%
ต	1	5.9%
ส	1	5.9%
ง	1	5.9%
ท	1	5.9%
Other values (4)	4	23.5%

Hiragana

Value	Count	Frequency (%)
の	7	41.2%
だ	2	11.8%
け	1	5.9%
も	1	5.9%
く	1	5.9%
と	1	5.9%
し	1	5.9%
ま	1	5.9%
あ	1	5.9%
よ	1	5.9%

Tamil

Value	Count	Frequency (%)
ா	3	23.1%
ன	2	15.4%
ு	2	15.4%
வ	1	7.7%
ல	1	7.7%
்	1	7.7%
ஜ	1	7.7%
ர	1	7.7%
ம	1	7.7%

Greek

Value	Count	Frequency (%)
ν	2	20.0%
Κ	1	10.0%
υ	1	10.0%
ό	1	10.0%
δ	1	10.0%
ο	1	10.0%
τ	1	10.0%
α	1	10.0%
ς	1	10.0%

Inherited

Value	Count	Frequency (%)
‌	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	72554	99.2%
CJK	160	0.2%
Cyrillic	127	0.2%
None	72	0.1%
Hangul	45	0.1%
Arabic	39	0.1%
Devanagari	35	< 0.1%
Katakana	28	< 0.1%
Hiragana	17	< 0.1%
Thai	17	< 0.1%
Other values (4)	22	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	8436	11.6%
e	7412	10.2%
a	4625	6.4%
o	4370	6.0%
r	3892	5.4%
n	3885	5.4%
i	3723	5.1%
t	3600	5.0%
s	2857	3.9%
h	2717	3.7%
Other values (71)	27037	37.3%

None

Value	Count	Frequency (%)
é	18	25.0%
à	4	5.6%
ó	4	5.6%
è	4	5.6%
á	3	4.2%
å	3	4.2%
í	3	4.2%
ñ	2	2.8%
ø	2	2.8%
ă	2	2.8%
Other values (24)	27	37.5%

Cyrillic

Value	Count	Frequency (%)
о	18	14.2%
е	10	7.9%
а	10	7.9%
р	9	7.1%
н	8	6.3%
л	7	5.5%
в	6	4.7%
и	6	4.7%
С	5	3.9%
б	4	3.1%
Other values (26)	44	34.6%

Arabic

Value	Count	Frequency (%)
ا	7	17.9%
ی	6	15.4%
ن	4	10.3%
د	3	7.7%
ر	3	7.7%
س	3	7.7%
ه	3	7.7%
م	2	5.1%
ب	2	5.1%
آ	1	2.6%
Other values (5)	5	12.8%

Hiragana

Value	Count	Frequency (%)
の	7	41.2%
だ	2	11.8%
け	1	5.9%
も	1	5.9%
く	1	5.9%
と	1	5.9%
し	1	5.9%
ま	1	5.9%
あ	1	5.9%
よ	1	5.9%

CJK

Value	Count	Frequency (%)
三	5	3.1%
的	4	2.5%
城	4	2.5%
十	3	1.9%
一	3	1.9%
人	3	1.9%
暴	2	1.2%
七	2	1.2%
之	2	1.2%
石	2	1.2%
Other values (113)	130	81.2%

Devanagari

Value	Count	Frequency (%)
ी	5	14.3%
क	4	11.4%
ा	3	8.6%
भ	2	5.7%
ह	2	5.7%
ि	2	5.7%
ल	2	5.7%
न	2	5.7%
द	2	5.7%
ए	1	2.9%
Other values (10)	10	28.6%

Punctuation

Value	Count	Frequency (%)
’	3	42.9%
–	2	28.6%
‧	1	14.3%
‌	1	14.3%

Tamil

Value	Count	Frequency (%)
ா	3	23.1%
ன	2	15.4%
ு	2	15.4%
வ	1	7.7%
ல	1	7.7%
்	1	7.7%
ஜ	1	7.7%
ர	1	7.7%
ம	1	7.7%

Hangul

Value	Count	Frequency (%)
놈	3	6.7%
이	2	4.4%
상	2	4.4%
한	2	4.4%
금	1	2.2%
자	1	2.2%
씨	1	2.2%
실	1	2.2%
올	1	2.2%
드	1	2.2%
Other values (30)	30	66.7%

Katakana

Value	Count	Frequency (%)
キ	3	10.7%
ア	2	7.1%
ラ	2	7.1%
ハ	2	7.1%
ン	2	7.1%
ゴ	1	3.6%
・	1	3.6%
シ	1	3.6%
ジ	1	3.6%
ポ	1	3.6%
Other values (12)	12	42.9%

Thai

Value	Count	Frequency (%)
ย	2	11.8%
ุ	2	11.8%
้	2	11.8%
ก	1	5.9%
ำ	1	5.9%
ม	1	5.9%
ต	1	5.9%
ส	1	5.9%
ง	1	5.9%
ท	1	5.9%
Other values (4)	4	23.5%

Latin Ext Additional

Value	Count	Frequency (%)
ợ	1	100.0%

Number Forms

Value	Count	Frequency (%)
⅓	1	100.0%

overview
Categorical

HIGH CARDINALITY UNIFORM

Distinct	4800
Distinct (%)	100.0%
Missing	3
Missing (%)	0.1%
Memory size	37.6 KiB

In the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization.	1
It's Yorkshire in 1974, and fear, mistrust and institutionalised police corruption are running riot. Rookie journalist Eddie Dunford is determined to search for the truth in an increasingly complex maze of lies and deceit surrounding the police investigation into a series of child abductions. When young Clare Kemplay goes missing, Eddie and his colleague, Barry, persuade their editor to let them investigate links with two similar abductions in the last decade. But after a mutilated body is found on a construction site owned by a local property magnate, Eddie and Barry are drawn into a deadly world of secrecy, intimidation, shocking revelations and police brutality.	1
The true story of Australia's cat-and-mouse underground mine warfare – one of the most misunderstood, misrepresented and mystifying conflicts of WW I. It was a secret struggle BENEATH the Western Front that combined daring engineering, technology and science, and few on the surface knew of the brave, claustrophobic and sometimes barbaric work of these tunnellers.	1
Simon Cable wakes up in a hospital bed, confused and disoriented. He soon discovers from doctors that he has amnesia and is unable to remember the last two years of his life. Cable investigates what has happened to him and slowly pieces together his enigmatic past.	1
A squad of Ultramarines answer a distress call from an Imperial Shrine World. A full Company of Imperial Fists was stationed there, but there is no answer from them. The squad investigates to find out what has happened there.	1
Other values (4795)	4795

Length

Max length	1000
Median length	625
Mean length	305.39875
Min length	1

Characters and Unicode

Total characters	1465914
Distinct characters	127
Distinct categories	19 ?
Distinct scripts	2 ?
Distinct blocks	6 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4800 ?
Unique (%)	100.0%

Sample

1st row	In the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization.
2nd row	Captain Barbossa, long believed to be dead, has come back to life and is headed to the edge of the Earth with Will Turner and Elizabeth Swann. But nothing is quite as it seems.
3rd row	A cryptic message from Bond’s past sends him on a trail to uncover a sinister organization. While M battles political forces to keep the secret service alive, Bond peels back the layers of deceit to reveal the terrible truth behind SPECTRE.
4th row	Following the death of District Attorney Harvey Dent, Batman assumes responsibility for Dent's crimes to protect the late attorney's reputation and is subsequently hunted by the Gotham City Police Department. Eight years later, Batman encounters the mysterious Selina Kyle and the villainous Bane, a new terrorist leader who overwhelms Gotham's finest. The Dark Knight resurfaces to protect a city that has branded him an enemy.
5th row	John Carter is a war-weary, former military captain who's inexplicably transported to the mysterious and exotic planet of Barsoom (Mars) and reluctantly becomes embroiled in an epic conflict. It's a world on the brink of collapse, and Carter rediscovers his humanity when he realizes the survival of Barsoom and its people rests in his hands.

Common Values

Value	Count	Frequency (%)
In the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization.	1	< 0.1%
It's Yorkshire in 1974, and fear, mistrust and institutionalised police corruption are running riot. Rookie journalist Eddie Dunford is determined to search for the truth in an increasingly complex maze of lies and deceit surrounding the police investigation into a series of child abductions. When young Clare Kemplay goes missing, Eddie and his colleague, Barry, persuade their editor to let them investigate links with two similar abductions in the last decade. But after a mutilated body is found on a construction site owned by a local property magnate, Eddie and Barry are drawn into a deadly world of secrecy, intimidation, shocking revelations and police brutality.	1	< 0.1%
The true story of Australia's cat-and-mouse underground mine warfare – one of the most misunderstood, misrepresented and mystifying conflicts of WW I. It was a secret struggle BENEATH the Western Front that combined daring engineering, technology and science, and few on the surface knew of the brave, claustrophobic and sometimes barbaric work of these tunnellers.	1	< 0.1%
Simon Cable wakes up in a hospital bed, confused and disoriented. He soon discovers from doctors that he has amnesia and is unable to remember the last two years of his life. Cable investigates what has happened to him and slowly pieces together his enigmatic past.	1	< 0.1%
A squad of Ultramarines answer a distress call from an Imperial Shrine World. A full Company of Imperial Fists was stationed there, but there is no answer from them. The squad investigates to find out what has happened there.	1	< 0.1%
When a New York reporter plucks crocodile hunter Dundee from the Australian Outback for a visit to the Big Apple, it's a clash of cultures and a recipe for good-natured comedy as naïve Dundee negotiates the concrete jungle. Dundee proves that his instincts are quite useful in the city and adeptly handles everything from wily muggers to high-society snoots without breaking a sweat.	1	< 0.1%
After a frantic suicide attempt, Veronika awakens inside a mysterious mental asylum. Under the supervision of an unorthodox psychiatrist who specializes in controversial treatment, Veronika learns that she has only weeks to live.	1	< 0.1%
The Girl on the Train is a 2009 French drama film directed by André Téchiné. Jeanne is a young woman, striking but otherwise without qualities. Her mother tries to get her a job in the office of a lawyer, Bleistein, her lover years ago. Jeanne fails the interview but falls into a relationship with Franck, a wrestler whose dreams and claims of being in a legitimate business partnership Jeanne is only too happy to believe. When Franck is arrested, he turns on Jeanne for her naivety; she's stung and seeks attention by making up a story of an attack on a train. Is there any way out for her?	1	< 0.1%
A group of aspiring entertainers try to establish careers for themselves in the city of Los Angeles.	1	< 0.1%
While undergoing heart surgery, a man experiences a phenomenon called ‘anesthetic awareness’, which leaves him awake but paralyzed throughout the operation. As various obstacles present themselves, his wife must make life-altering decisions while wrestling with her own personal drama.	1	< 0.1%
Other values (4790)	4790	99.7%
(Missing)	3	0.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
the	13894	5.5%
a	10452	4.2%
to	7925	3.2%
and	7388	3.0%
of	6867	2.7%
in	4536	1.8%
his	3994	1.6%
is	3369	1.3%
with	2533	1.0%
her	2163	0.9%
Other values (24224)	187234	74.8%

Most occurring characters

Value	Count	Frequency (%)
	245712	16.8%
e	141178	9.6%
t	97104	6.6%
a	94907	6.5%
i	85329	5.8%
o	84373	5.8%
n	84015	5.7%
s	78343	5.3%
r	77154	5.3%
h	61948	4.2%
Other values (117)	415851	28.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1139845	77.8%
Space Separator	245716	16.8%
Uppercase Letter	39039	2.7%
Other Punctuation	30988	2.1%
Dash Punctuation	4474	0.3%
Decimal Number	3915	0.3%
Open Punctuation	757	0.1%
Close Punctuation	754	0.1%
Final Punctuation	310	< 0.1%
Initial Punctuation	49	< 0.1%
Other values (9)	67	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	141178	12.4%
t	97104	8.5%
a	94907	8.3%
i	85329	7.5%
o	84373	7.4%
n	84015	7.4%
s	78343	6.9%
r	77154	6.8%
h	61948	5.4%
l	48681	4.3%
Other values (36)	286813	25.2%

Uppercase Letter

Value	Count	Frequency (%)
A	4448	11.4%
T	3268	8.4%
S	2934	7.5%
B	2671	6.8%
C	2467	6.3%
M	2307	5.9%
W	2098	5.4%
H	1808	4.6%
D	1682	4.3%
I	1604	4.1%
Other values (18)	13752	35.2%

Other Punctuation

Value	Count	Frequency (%)
,	13388	43.2%
.	12056	38.9%
'	3577	11.5%
"	1021	3.3%
:	284	0.9%
?	218	0.7%
;	175	0.6%
!	142	0.5%
/	57	0.2%
…	35	0.1%
Other values (5)	35	0.1%

Decimal Number

Value	Count	Frequency (%)
1	926	23.7%
0	821	21.0%
9	568	14.5%
2	371	9.5%
5	231	5.9%
7	224	5.7%
8	206	5.3%
3	199	5.1%
4	189	4.8%
6	180	4.6%

Dash Punctuation

Value	Count	Frequency (%)
-	4206	94.0%
–	205	4.6%
—	62	1.4%
―	1	< 0.1%

Math Symbol

Value	Count	Frequency (%)
+	2	40.0%
−	1	20.0%
~	1	20.0%
\|	1	20.0%

Space Separator

Value	Count	Frequency (%)
	245712	> 99.9%
	4	< 0.1%

Open Punctuation

Value	Count	Frequency (%)
(	755	99.7%
[	2	0.3%

Close Punctuation

Value	Count	Frequency (%)
)	753	99.9%
]	1	0.1%

Final Punctuation

Value	Count	Frequency (%)
’	275	88.7%
”	35	11.3%

Currency Symbol

Value	Count	Frequency (%)
$	45	97.8%
£	1	2.2%

Initial Punctuation

Value	Count	Frequency (%)
“	35	71.4%
‘	14	28.6%

Other Symbol

Value	Count	Frequency (%)
®	3	75.0%
¦	1	25.0%

Format

Value	Count	Frequency (%)
	3	100.0%

Control

Value	Count	Frequency (%)
	3	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	3	100.0%

Modifier Letter

Value	Count	Frequency (%)
ʼ	1	100.0%

Other Number

Value	Count	Frequency (%)
¹	1	100.0%

Modifier Symbol

Value	Count	Frequency (%)
`	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1178884	80.4%
Common	287030	19.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	141178	12.0%
t	97104	8.2%
a	94907	8.1%
i	85329	7.2%
o	84373	7.2%
n	84015	7.1%
s	78343	6.6%
r	77154	6.5%
h	61948	5.3%
l	48681	4.1%
Other values (64)	325852	27.6%

Common

Value	Count	Frequency (%)
	245712	85.6%
,	13388	4.7%
.	12056	4.2%
-	4206	1.5%
'	3577	1.2%
"	1021	0.4%
1	926	0.3%
0	821	0.3%
(	755	0.3%
)	753	0.3%
Other values (43)	3815	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1465079	99.9%
Punctuation	662	< 0.1%
None	170	< 0.1%
Modifier Letters	1	< 0.1%
Alphabetic PF	1	< 0.1%
Math Operators	1	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	245712	16.8%
e	141178	9.6%
t	97104	6.6%
a	94907	6.5%
i	85329	5.8%
o	84373	5.8%
n	84015	5.7%
s	78343	5.3%
r	77154	5.3%
h	61948	4.2%
Other values (77)	415016	28.3%

Punctuation

Value	Count	Frequency (%)
’	275	41.5%
–	205	31.0%
—	62	9.4%
…	35	5.3%
“	35	5.3%
”	35	5.3%
‘	14	2.1%
―	1	0.2%

None

Value	Count	Frequency (%)
é	92	54.1%
á	12	7.1%
ó	8	4.7%
è	4	2.4%
ö	4	2.4%
ç	4	2.4%
ï	4	2.4%
í	4	2.4%
	4	2.4%
ñ	3	1.8%
Other values (19)	31	18.2%

Modifier Letters

Value	Count	Frequency (%)
ʼ	1	100.0%

Alphabetic PF

Value	Count	Frequency (%)
ﬁ	1	100.0%

Math Operators

Value	Count	Frequency (%)
−	1	100.0%

popularity
Real number (ℝ)

Distinct	4802
Distinct (%)	> 99.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	21.492301

Minimum	0
Maximum	875.58131
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	37.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0.3628167
Q1	4.66807
median	12.921594
Q3	28.313505
95-th percentile	67.385962
Maximum	875.58131
Range	875.58131
Interquartile range (IQR)	23.645435

Descriptive statistics

Standard deviation	31.81665
Coefficient of variation (CV)	1.4803743
Kurtosis	191.99582
Mean	21.492301
Median Absolute Deviation (MAD)	9.814445
Skewness	9.7214159
Sum	103227.52
Variance	1012.2992
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
8.902102	2	< 0.1%
150.437577	1	< 0.1%
7.247023	1	< 0.1%
14.038703	1	< 0.1%
3.949796	1	< 0.1%
3.789485	1	< 0.1%
3.891186	1	< 0.1%
16.072466	1	< 0.1%
4.799022	1	< 0.1%
2.351706	1	< 0.1%
Other values (4792)	4792	99.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1	< 0.1%
0.000372	1	< 0.1%
0.001117	1	< 0.1%
0.001186	1	< 0.1%
0.001389	1	< 0.1%
0.001586	1	< 0.1%
0.002386	1	< 0.1%
0.002388	1	< 0.1%
0.003142	1	< 0.1%
0.003352	1	< 0.1%

Value	Count	Frequency (%)
875.581305	1	< 0.1%
724.247784	1	< 0.1%
514.569956	1	< 0.1%
481.098624	1	< 0.1%
434.278564	1	< 0.1%
418.708552	1	< 0.1%
271.972889	1	< 0.1%
243.791743	1	< 0.1%
206.227151	1	< 0.1%
203.73459	1	< 0.1%

production_companies
Categorical

Distinct	3697
Distinct (%)	77.0%
Missing	0
Missing (%)	0.0%
Memory size	37.6 KiB

[]	351
[{"name": "Paramount Pictures", "id": 4}]	58
[{"name": "Universal Pictures", "id": 33}]	45
[{"name": "New Line Cinema", "id": 12}]	38
[{"name": "Columbia Pictures", "id": 5}]	37
Other values (3692)	4274

Length

Max length	1155
Median length	469
Mean length	128.01499
Min length	2

Characters and Unicode

Total characters	614856
Distinct characters	83
Distinct categories	9 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3497 ?
Unique (%)	72.8%

Sample

1st row	[{"name": "Ingenious Film Partners", "id": 289}, {"name": "Twentieth Century Fox Film Corporation", "id": 306}, {"name": "Dune Entertainment", "id": 444}, {"name": "Lightstorm Entertainment", "id": 574}]
2nd row	[{"name": "Walt Disney Pictures", "id": 2}, {"name": "Jerry Bruckheimer Films", "id": 130}, {"name": "Second Mate Productions", "id": 19936}]
3rd row	[{"name": "Columbia Pictures", "id": 5}, {"name": "Danjaq", "id": 10761}, {"name": "B24", "id": 69434}]
4th row	[{"name": "Legendary Pictures", "id": 923}, {"name": "Warner Bros.", "id": 6194}, {"name": "DC Entertainment", "id": 9993}, {"name": "Syncopy", "id": 9996}]
5th row	[{"name": "Walt Disney Pictures", "id": 2}]

Common Values

Value	Count	Frequency (%)
[]	351	7.3%
[{"name": "Paramount Pictures", "id": 4}]	58	1.2%
[{"name": "Universal Pictures", "id": 33}]	45	0.9%
[{"name": "New Line Cinema", "id": 12}]	38	0.8%
[{"name": "Columbia Pictures", "id": 5}]	37	0.8%
[{"name": "Metro-Goldwyn-Mayer (MGM)", "id": 8411}]	32	0.7%
[{"name": "Twentieth Century Fox Film Corporation", "id": 306}]	31	0.6%
[{"name": "Warner Bros.", "id": 6194}]	27	0.6%
[{"name": "Walt Disney Pictures", "id": 2}]	27	0.6%
[{"name": "Touchstone Pictures", "id": 9195}]	26	0.5%
Other values (3687)	4131	86.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
name	13677	18.1%
id	13677	18.1%
pictures	2584	3.4%
films	1883	2.5%
productions	1830	2.4%
entertainment	1567	2.1%
film	915	1.2%
	538	0.7%
corporation	404	0.5%
fox	372	0.5%
Other values (10124)	38291	50.6%

Most occurring characters

Value	Count	Frequency (%)
"	82064	13.3%
	70935	11.5%
i	34526	5.6%
e	34198	5.6%
n	32605	5.3%
a	28315	4.6%
:	27355	4.4%
,	22976	3.7%
m	22254	3.6%
d	19878	3.2%
Other values (73)	239750	39.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	279221	45.4%
Other Punctuation	134101	21.8%
Space Separator	70935	11.5%
Decimal Number	54691	8.9%
Uppercase Letter	37429	6.1%
Close Punctuation	18933	3.1%
Open Punctuation	18933	3.1%
Dash Punctuation	500	0.1%
Math Symbol	113	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
i	34526	12.4%
e	34198	12.2%
n	32605	11.7%
a	28315	10.1%
m	22254	8.0%
d	19878	7.1%
t	18386	6.6%
r	17181	6.2%
o	15560	5.6%
s	12762	4.6%
Other values (16)	43556	15.6%

Uppercase Letter

Value	Count	Frequency (%)
P	6167	16.5%
F	4436	11.9%
C	3700	9.9%
M	2429	6.5%
E	2337	6.2%
S	2241	6.0%
T	1644	4.4%
B	1566	4.2%
A	1427	3.8%
G	1409	3.8%
Other values (16)	10073	26.9%

Other Punctuation

Value	Count	Frequency (%)
"	82064	61.2%
:	27355	20.4%
,	22976	17.1%
.	835	0.6%
\	455	0.3%
/	176	0.1%
&	161	0.1%
'	71	0.1%
!	4	< 0.1%
@	2	< 0.1%
Other values (2)	2	< 0.1%

Decimal Number

Value	Count	Frequency (%)
1	8454	15.5%
2	6455	11.8%
3	5968	10.9%
4	5535	10.1%
0	5406	9.9%
5	4943	9.0%
6	4700	8.6%
9	4577	8.4%
7	4350	8.0%
8	4303	7.9%

Close Punctuation

Value	Count	Frequency (%)
}	13677	72.2%
]	4803	25.4%
)	453	2.4%

Open Punctuation

Value	Count	Frequency (%)
{	13677	72.2%
[	4803	25.4%
(	453	2.4%

Space Separator

Value	Count	Frequency (%)
	70935	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	500	100.0%

Math Symbol

Value	Count	Frequency (%)
+	113	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	316650	51.5%
Common	298206	48.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
i	34526	10.9%
e	34198	10.8%
n	32605	10.3%
a	28315	8.9%
m	22254	7.0%
d	19878	6.3%
t	18386	5.8%
r	17181	5.4%
o	15560	4.9%
s	12762	4.0%
Other values (42)	80985	25.6%

Common

Value	Count	Frequency (%)
"	82064	27.5%
	70935	23.8%
:	27355	9.2%
,	22976	7.7%
}	13677	4.6%
{	13677	4.6%
1	8454	2.8%
2	6455	2.2%
3	5968	2.0%
4	5535	1.9%
Other values (21)	41110	13.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	614856	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
"	82064	13.3%
	70935	11.5%
i	34526	5.6%
e	34198	5.6%
n	32605	5.3%
a	28315	4.6%
:	27355	4.4%
,	22976	3.7%
m	22254	3.6%
d	19878	3.2%
Other values (73)	239750	39.0%

production_countries
Categorical

HIGH CARDINALITY IMBALANCE

Distinct	469
Distinct (%)	9.8%
Missing	0
Missing (%)	0.0%
Memory size	37.6 KiB

[{"iso_3166_1": "US", "name": "United States of America"}]	2977
[{"iso_3166_1": "GB", "name": "United Kingdom"}, {"iso_3166_1": "US", "name": "United States of America"}]	181
[]	174
[{"iso_3166_1": "GB", "name": "United Kingdom"}]	131
[{"iso_3166_1": "DE", "name": "Germany"}, {"iso_3166_1": "US", "name": "United States of America"}]	119
Other values (464)	1221

Length

Max length	517
Median length	58
Mean length	69.921299
Min length	2

Characters and Unicode

Total characters	335832
Distinct characters	61
Distinct categories	8 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	353 ?
Unique (%)	7.3%

Sample

1st row	[{"iso_3166_1": "US", "name": "United States of America"}, {"iso_3166_1": "GB", "name": "United Kingdom"}]
2nd row	[{"iso_3166_1": "US", "name": "United States of America"}]
3rd row	[{"iso_3166_1": "GB", "name": "United Kingdom"}, {"iso_3166_1": "US", "name": "United States of America"}]
4th row	[{"iso_3166_1": "US", "name": "United States of America"}]
5th row	[{"iso_3166_1": "US", "name": "United States of America"}]

Common Values

Value	Count	Frequency (%)
[{"iso_3166_1": "US", "name": "United States of America"}]	2977	62.0%
[{"iso_3166_1": "GB", "name": "United Kingdom"}, {"iso_3166_1": "US", "name": "United States of America"}]	181	3.8%
[]	174	3.6%
[{"iso_3166_1": "GB", "name": "United Kingdom"}]	131	2.7%
[{"iso_3166_1": "DE", "name": "Germany"}, {"iso_3166_1": "US", "name": "United States of America"}]	119	2.5%
[{"iso_3166_1": "CA", "name": "Canada"}, {"iso_3166_1": "US", "name": "United States of America"}]	88	1.8%
[{"iso_3166_1": "FR", "name": "France"}]	49	1.0%
[{"iso_3166_1": "AU", "name": "Australia"}, {"iso_3166_1": "US", "name": "United States of America"}]	46	1.0%
[{"iso_3166_1": "CA", "name": "Canada"}]	46	1.0%
[{"iso_3166_1": "FR", "name": "France"}, {"iso_3166_1": "US", "name": "United States of America"}]	38	0.8%
Other values (459)	954	19.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
iso_3166_1	6436	16.7%
name	6436	16.7%
united	4606	11.9%
of	3956	10.2%
america	3956	10.2%
us	3956	10.2%
states	3956	10.2%
kingdom	636	1.6%
gb	636	1.6%
de	324	0.8%
Other values (180)	3698	9.6%

Most occurring characters

Value	Count	Frequency (%)
"	51488	15.3%
	33793	10.1%
e	19992	6.0%
a	16820	5.0%
i	16187	4.8%
n	13165	3.9%
_	12872	3.8%
1	12872	3.8%
6	12872	3.8%
:	12872	3.8%
Other values (51)	132899	39.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	133878	39.9%
Other Punctuation	72603	21.6%
Space Separator	33793	10.1%
Decimal Number	32180	9.6%
Uppercase Letter	28028	8.3%
Connector Punctuation	12872	3.8%
Open Punctuation	11239	3.3%
Close Punctuation	11239	3.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	19992	14.9%
a	16820	12.6%
i	16187	12.1%
n	13165	9.8%
t	12819	9.6%
m	11448	8.6%
o	11294	8.4%
s	10601	7.9%
d	5708	4.3%
r	4964	3.7%
Other values (15)	10880	8.1%

Uppercase Letter

Value	Count	Frequency (%)
U	8717	31.1%
S	8175	29.2%
A	4550	16.2%
G	979	3.5%
K	802	2.9%
B	735	2.6%
C	723	2.6%
F	625	2.2%
E	511	1.8%
R	443	1.6%
Other values (14)	1768	6.3%

Other Punctuation

Value	Count	Frequency (%)
"	51488	70.9%
:	12872	17.7%
,	8243	11.4%

Decimal Number

Value	Count	Frequency (%)
1	12872	40.0%
6	12872	40.0%
3	6436	20.0%

Open Punctuation

Value	Count	Frequency (%)
{	6436	57.3%
[	4803	42.7%

Close Punctuation

Value	Count	Frequency (%)
}	6436	57.3%
]	4803	42.7%

Space Separator

Value	Count	Frequency (%)
	33793	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	12872	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	173926	51.8%
Latin	161906	48.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	19992	12.3%
a	16820	10.4%
i	16187	10.0%
n	13165	8.1%
t	12819	7.9%
m	11448	7.1%
o	11294	7.0%
s	10601	6.5%
U	8717	5.4%
S	8175	5.0%
Other values (39)	32688	20.2%

Common

Value	Count	Frequency (%)
"	51488	29.6%
	33793	19.4%
_	12872	7.4%
1	12872	7.4%
6	12872	7.4%
:	12872	7.4%
,	8243	4.7%
{	6436	3.7%
3	6436	3.7%
}	6436	3.7%
Other values (2)	9606	5.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	335832	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
"	51488	15.3%
	33793	10.1%
e	19992	6.0%
a	16820	5.0%
i	16187	4.8%
n	13165	3.9%
_	12872	3.8%
1	12872	3.8%
6	12872	3.8%
:	12872	3.8%
Other values (51)	132899	39.6%

release_date
Categorical

HIGH CARDINALITY UNIFORM

Distinct	3280
Distinct (%)	68.3%
Missing	1
Missing (%)	< 0.1%
Memory size	37.6 KiB

2006-01-01	10
2002-01-01	8
2004-09-03	7
2013-07-18	7
2014-12-25	7
Other values (3275)	4763

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	48020
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2264 ?
Unique (%)	47.1%

Sample

1st row	2009-12-10
2nd row	2007-05-19
3rd row	2015-10-26
4th row	2012-07-16
5th row	2012-03-07

Common Values

Value	Count	Frequency (%)
2006-01-01	10	0.2%
2002-01-01	8	0.2%
2004-09-03	7	0.1%
2013-07-18	7	0.1%
2014-12-25	7	0.1%
1999-10-22	7	0.1%
2005-09-16	6	0.1%
2005-01-01	6	0.1%
2003-01-01	6	0.1%
2007-01-01	6	0.1%
Other values (3270)	4732	98.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2006-01-01	10	0.2%
2002-01-01	8	0.2%
2004-09-03	7	0.1%
2013-07-18	7	0.1%
2014-12-25	7	0.1%
1999-10-22	7	0.1%
2007-01-01	6	0.1%
2011-09-16	6	0.1%
2015-10-16	6	0.1%
2011-09-30	6	0.1%
Other values (3270)	4732	98.5%

Most occurring characters

Value	Count	Frequency (%)
0	11926	24.8%
-	9604	20.0%
1	7613	15.9%
2	6733	14.0%
9	3583	7.5%
3	1532	3.2%
8	1521	3.2%
5	1450	3.0%
6	1411	2.9%
4	1333	2.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	38416	80.0%
Dash Punctuation	9604	20.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	11926	31.0%
1	7613	19.8%
2	6733	17.5%
9	3583	9.3%
3	1532	4.0%
8	1521	4.0%
5	1450	3.8%
6	1411	3.7%
4	1333	3.5%
7	1314	3.4%

Dash Punctuation

Value	Count	Frequency (%)
-	9604	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	48020	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	11926	24.8%
-	9604	20.0%
1	7613	15.9%
2	6733	14.0%
9	3583	7.5%
3	1532	3.2%
8	1521	3.2%
5	1450	3.0%
6	1411	2.9%
4	1333	2.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	48020	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	11926	24.8%
-	9604	20.0%
1	7613	15.9%
2	6733	14.0%
9	3583	7.5%
3	1532	3.2%
8	1521	3.2%
5	1450	3.0%
6	1411	2.9%
4	1333	2.8%

revenue
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	3297
Distinct (%)	68.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	82260639

Minimum	0
Maximum	2.7879651 × 10⁹
Zeros	1427
Zeros (%)	29.7%
Negative	0
Negative (%)	0.0%
Memory size	37.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	19170001
Q3	92917187
95-th percentile	3.692849 × 10⁸
Maximum	2.7879651 × 10⁹
Range	2.7879651 × 10⁹
Interquartile range (IQR)	92917187

Descriptive statistics

Standard deviation	1.628571 × 10⁸
Coefficient of variation (CV)	1.9797695
Kurtosis	33.12363
Mean	82260639
Median Absolute Deviation (MAD)	19170001
Skewness	4.4447164
Sum	3.9509785 × 10¹¹
Variance	2.6522435 × 10¹⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1427	29.7%
7000000	6	0.1%
8000000	6	0.1%
6000000	5	0.1%
12000000	5	0.1%
10000000	5	0.1%
100000000	5	0.1%
14000000	4	0.1%
11000000	4	0.1%
5000000	4	0.1%
Other values (3287)	3332	69.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1427	29.7%
5	1	< 0.1%
7	2	< 0.1%
10	1	< 0.1%
11	2	< 0.1%
12	2	< 0.1%
13	1	< 0.1%
14	1	< 0.1%
15	1	< 0.1%
16	1	< 0.1%

Value	Count	Frequency (%)
2787965087	1	< 0.1%
1845034188	1	< 0.1%
1519557910	1	< 0.1%
1513528810	1	< 0.1%
1506249360	1	< 0.1%
1405403694	1	< 0.1%
1274219009	1	< 0.1%
1215439994	1	< 0.1%
1156730962	1	< 0.1%
1153304495	1	< 0.1%

runtime
Real number (ℝ)

Distinct	156
Distinct (%)	3.2%
Missing	2
Missing (%)	< 0.1%
Infinite	0
Infinite (%)	0.0%
Mean	106.87586

Minimum	0
Maximum	338
Zeros	35
Zeros (%)	0.7%
Negative	0
Negative (%)	0.0%
Memory size	37.6 KiB

Quantile statistics

Minimum	0
5-th percentile	83
Q1	94
median	103
Q3	118
95-th percentile	144
Maximum	338
Range	338
Interquartile range (IQR)	24

Descriptive statistics

Standard deviation	22.611935
Coefficient of variation (CV)	0.21157196
Kurtosis	8.9354488
Mean	106.87586
Median Absolute Deviation (MAD)	11
Skewness	0.71595651
Sum	513111
Variance	511.29959
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
90	163	3.4%
100	149	3.1%
98	140	2.9%
97	133	2.8%
95	123	2.6%
99	119	2.5%
94	116	2.4%
96	115	2.4%
101	114	2.4%
93	113	2.4%
Other values (146)	3516	73.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	35	0.7%
14	1	< 0.1%
25	1	< 0.1%
41	1	< 0.1%
42	1	< 0.1%
46	1	< 0.1%
47	1	< 0.1%
53	1	< 0.1%
59	1	< 0.1%
60	1	< 0.1%

Value	Count	Frequency (%)
338	1	< 0.1%
276	1	< 0.1%
254	1	< 0.1%
248	1	< 0.1%
242	1	< 0.1%
240	1	< 0.1%
238	1	< 0.1%
229	1	< 0.1%
225	1	< 0.1%
219	1	< 0.1%

spoken_languages
Categorical

HIGH CARDINALITY IMBALANCE

Distinct	544
Distinct (%)	11.3%
Missing	0
Missing (%)	0.0%
Memory size	37.6 KiB

[{"iso_639_1": "en", "name": "English"}]	3171
[{"iso_639_1": "en", "name": "English"}, {"iso_639_1": "es", "name": "Espa\u00f1ol"}]	127
[{"iso_639_1": "en", "name": "English"}, {"iso_639_1": "fr", "name": "Fran\u00e7ais"}]	114
[]	86
[{"iso_639_1": "es", "name": "Espa\u00f1ol"}, {"iso_639_1": "en", "name": "English"}]	54
Other values (539)	1251

Length

Max length	474
Median length	40
Mean length	62.923381
Min length	2

Characters and Unicode

Total characters	302221
Distinct characters	68
Distinct categories	8 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	416 ?
Unique (%)	8.7%

Sample

1st row	[{"iso_639_1": "en", "name": "English"}, {"iso_639_1": "es", "name": "Espa\u00f1ol"}]
2nd row	[{"iso_639_1": "en", "name": "English"}]
3rd row	[{"iso_639_1": "fr", "name": "Fran\u00e7ais"}, {"iso_639_1": "en", "name": "English"}, {"iso_639_1": "es", "name": "Espa\u00f1ol"}, {"iso_639_1": "it", "name": "Italiano"}, {"iso_639_1": "de", "name": "Deutsch"}]
4th row	[{"iso_639_1": "en", "name": "English"}]
5th row	[{"iso_639_1": "en", "name": "English"}]

Common Values

Value	Count	Frequency (%)
[{"iso_639_1": "en", "name": "English"}]	3171	66.0%
[{"iso_639_1": "en", "name": "English"}, {"iso_639_1": "es", "name": "Espa\u00f1ol"}]	127	2.6%
[{"iso_639_1": "en", "name": "English"}, {"iso_639_1": "fr", "name": "Fran\u00e7ais"}]	114	2.4%
[]	86	1.8%
[{"iso_639_1": "es", "name": "Espa\u00f1ol"}, {"iso_639_1": "en", "name": "English"}]	54	1.1%
[{"iso_639_1": "en", "name": "English"}, {"iso_639_1": "de", "name": "Deutsch"}]	53	1.1%
[{"iso_639_1": "en", "name": "English"}, {"iso_639_1": "it", "name": "Italiano"}]	51	1.1%
[{"iso_639_1": "en", "name": "English"}, {"iso_639_1": "ru", "name": "P\u0443\u0441\u0441\u043a\u0438\u0439"}]	50	1.0%
[{"iso_639_1": "fr", "name": "Fran\u00e7ais"}]	49	1.0%
[{"iso_639_1": "es", "name": "Espa\u00f1ol"}]	23	0.5%
Other values (534)	1025	21.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
iso_639_1	6937	24.8%
name	6937	24.8%
english	4485	16.0%
en	4485	16.0%
fr	437	1.6%
fran\u00e7ais	437	1.6%
es	351	1.3%
espa\u00f1ol	351	1.3%
deutsch	262	0.9%
de	262	0.9%
Other values (144)	3010	10.8%

Most occurring characters

Value	Count	Frequency (%)
"	55496	18.4%
	23151	7.7%
n	16768	5.5%
e	13992	4.6%
:	13874	4.6%
_	13874	4.6%
s	13221	4.4%
i	12537	4.1%
a	9800	3.2%
,	9157	3.0%
Other values (58)	120351	39.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	108442	35.9%
Other Punctuation	83645	27.7%
Decimal Number	43345	14.3%
Space Separator	23151	7.7%
Connector Punctuation	13874	4.6%
Close Punctuation	11740	3.9%
Open Punctuation	11740	3.9%
Uppercase Letter	6284	2.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	16768	15.5%
e	13992	12.9%
s	13221	12.2%
i	12537	11.6%
a	9800	9.0%
o	7712	7.1%
m	6969	6.4%
u	5701	5.3%
l	5259	4.8%
h	5047	4.7%
Other values (16)	11436	10.5%

Uppercase Letter

Value	Count	Frequency (%)
E	4840	77.0%
F	437	7.0%
P	306	4.9%
D	276	4.4%
I	188	3.0%
L	54	0.9%
M	42	0.7%
T	35	0.6%
N	25	0.4%
V	17	0.3%
Other values (10)	64	1.0%

Decimal Number

Value	Count	Frequency (%)
3	8367	19.3%
1	8142	18.8%
6	8130	18.8%
9	7940	18.3%
0	5276	12.2%
4	2368	5.5%
7	872	2.0%
5	776	1.8%
2	776	1.8%
8	698	1.6%

Other Punctuation

Value	Count	Frequency (%)
"	55496	66.3%
:	13874	16.6%
,	9157	10.9%
\	5033	6.0%
/	79	0.1%
?	6	< 0.1%

Close Punctuation

Value	Count	Frequency (%)
}	6937	59.1%
]	4803	40.9%

Open Punctuation

Value	Count	Frequency (%)
{	6937	59.1%
[	4803	40.9%

Space Separator

Value	Count	Frequency (%)
	23151	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	13874	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	187495	62.0%
Latin	114726	38.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	16768	14.6%
e	13992	12.2%
s	13221	11.5%
i	12537	10.9%
a	9800	8.5%
o	7712	6.7%
m	6969	6.1%
u	5701	5.0%
l	5259	4.6%
h	5047	4.4%
Other values (36)	17720	15.4%

Common

Value	Count	Frequency (%)
"	55496	29.6%
	23151	12.3%
:	13874	7.4%
_	13874	7.4%
,	9157	4.9%
3	8367	4.5%
1	8142	4.3%
6	8130	4.3%
9	7940	4.2%
}	6937	3.7%
Other values (12)	32427	17.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	302221	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
"	55496	18.4%
	23151	7.7%
n	16768	5.5%
e	13992	4.6%
:	13874	4.6%
_	13874	4.6%
s	13221	4.4%
i	12537	4.1%
a	9800	3.2%
,	9157	3.0%
Other values (58)	120351	39.8%

status
Categorical

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	37.6 KiB

Released	4795
Rumored	5
Post Production	3

Length

Max length	15
Median length	8
Mean length	8.0033313
Min length	7

Characters and Unicode

Total characters	38440
Distinct characters	16
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Released
2nd row	Released
3rd row	Released
4th row	Released
5th row	Released

Common Values

Value	Count	Frequency (%)
Released	4795	99.8%
Rumored	5	0.1%
Post Production	3	0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
released	4795	99.8%
rumored	5	0.1%
post	3	0.1%
production	3	0.1%

Most occurring characters

Value	Count	Frequency (%)
e	14390	37.4%
d	4803	12.5%
R	4800	12.5%
s	4798	12.5%
l	4795	12.5%
a	4795	12.5%
o	14	< 0.1%
u	8	< 0.1%
r	8	< 0.1%
P	6	< 0.1%
Other values (6)	23	0.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	33631	87.5%
Uppercase Letter	4806	12.5%
Space Separator	3	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	14390	42.8%
d	4803	14.3%
s	4798	14.3%
l	4795	14.3%
a	4795	14.3%
o	14	< 0.1%
u	8	< 0.1%
r	8	< 0.1%
t	6	< 0.1%
m	5	< 0.1%
Other values (3)	9	< 0.1%

Uppercase Letter

Value	Count	Frequency (%)
R	4800	99.9%
P	6	0.1%

Space Separator

Value	Count	Frequency (%)
	3	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	38437	> 99.9%
Common	3	< 0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	14390	37.4%
d	4803	12.5%
R	4800	12.5%
s	4798	12.5%
l	4795	12.5%
a	4795	12.5%
o	14	< 0.1%
u	8	< 0.1%
r	8	< 0.1%
P	6	< 0.1%
Other values (5)	20	0.1%

Common

Value	Count	Frequency (%)
	3	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	38440	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	14390	37.4%
d	4803	12.5%
R	4800	12.5%
s	4798	12.5%
l	4795	12.5%
a	4795	12.5%
o	14	< 0.1%
u	8	< 0.1%
r	8	< 0.1%
P	6	< 0.1%
Other values (6)	23	0.1%

tagline
Categorical

HIGH CARDINALITY MISSING UNIFORM

Distinct	3944
Distinct (%)	99.6%
Missing	844
Missing (%)	17.6%
Memory size	37.6 KiB

Based on a true story.	3
Who's next?	2
Based on the incredible true story.	2
There are two sides to every love story.	2
One ordinary couple. One little white lie.	2
Other values (3939)	3948

Length

Max length	252
Median length	149
Mean length	41.988886
Min length	3

Characters and Unicode

Total characters	166234
Distinct characters	92
Distinct categories	11 ?
Distinct scripts	3 ?
Distinct blocks	4 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3930 ?
Unique (%)	99.3%

Sample

1st row	Enter the World of Pandora.
2nd row	At the end of the world, the adventure begins.
3rd row	A Plan No One Escapes
4th row	The Legend Ends
5th row	Lost in our world, found in another.

Common Values

Value	Count	Frequency (%)
Based on a true story.	3	0.1%
Who's next?	2	< 0.1%
Based on the incredible true story.	2	< 0.1%
There are two sides to every love story.	2	< 0.1%
One ordinary couple. One little white lie.	2	< 0.1%
What could go wrong?	2	< 0.1%
Who is John Galt?	2	< 0.1%
The only way out is down.	2	< 0.1%
Worlds Collide	2	< 0.1%
Be careful what you wish for.	2	< 0.1%
Other values (3934)	3938	82.0%
(Missing)	844	17.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
the	1880	6.1%
a	1085	3.5%
to	705	2.3%
is	653	2.1%
of	620	2.0%
you	535	1.7%
in	443	1.4%
and	328	1.1%
for	323	1.0%
it	310	1.0%
Other values (4349)	23980	77.7%

Most occurring characters

Value	Count	Frequency (%)
	26926	16.2%
e	17450	10.5%
o	10463	6.3%
t	10358	6.2%
a	8761	5.3%
n	8406	5.1%
i	8137	4.9%
r	7933	4.8%
s	7648	4.6%
h	6587	4.0%
Other values (82)	53565	32.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	121321	73.0%
Space Separator	26926	16.2%
Uppercase Letter	9700	5.8%
Other Punctuation	7563	4.5%
Decimal Number	521	0.3%
Dash Punctuation	150	0.1%
Final Punctuation	28	< 0.1%
Open Punctuation	8	< 0.1%
Close Punctuation	8	< 0.1%
Other Letter	5	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	17450	14.4%
o	10463	8.6%
t	10358	8.5%
a	8761	7.2%
n	8406	6.9%
i	8137	6.7%
r	7933	6.5%
s	7648	6.3%
h	6587	5.4%
l	5132	4.2%
Other values (18)	30446	25.1%

Uppercase Letter

Value	Count	Frequency (%)
T	1492	15.4%
A	827	8.5%
S	708	7.3%
I	599	6.2%
W	592	6.1%
H	585	6.0%
B	478	4.9%
N	430	4.4%
F	419	4.3%
E	411	4.2%
Other values (16)	3159	32.6%

Other Punctuation

Value	Count	Frequency (%)
.	5147	68.1%
'	1039	13.7%
,	725	9.6%
!	356	4.7%
?	220	2.9%
"	20	0.3%
:	14	0.2%
…	10	0.1%
&	9	0.1%
%	9	0.1%
Other values (4)	14	0.2%

Decimal Number

Value	Count	Frequency (%)
0	162	31.1%
1	99	19.0%
2	55	10.6%
9	38	7.3%
3	37	7.1%
7	28	5.4%
5	27	5.2%
4	26	5.0%
6	25	4.8%
8	24	4.6%

Other Letter

Value	Count	Frequency (%)
的	1	20.0%
者	1	20.0%
舞	1	20.0%
后	1	20.0%
最	1	20.0%

Dash Punctuation

Value	Count	Frequency (%)
-	149	99.3%
–	1	0.7%

Open Punctuation

Value	Count	Frequency (%)
(	7	87.5%
[	1	12.5%

Close Punctuation

Value	Count	Frequency (%)
)	7	87.5%
]	1	12.5%

Space Separator

Value	Count	Frequency (%)
	26926	100.0%

Final Punctuation

Value	Count	Frequency (%)
’	28	100.0%

Currency Symbol

Value	Count	Frequency (%)
$	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	131021	78.8%
Common	35208	21.2%
Han	5	< 0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	17450	13.3%
o	10463	8.0%
t	10358	7.9%
a	8761	6.7%
n	8406	6.4%
i	8137	6.2%
r	7933	6.1%
s	7648	5.8%
h	6587	5.0%
l	5132	3.9%
Other values (44)	40146	30.6%

Common

Value	Count	Frequency (%)
	26926	76.5%
.	5147	14.6%
'	1039	3.0%
,	725	2.1%
!	356	1.0%
?	220	0.6%
0	162	0.5%
-	149	0.4%
1	99	0.3%
2	55	0.2%
Other values (23)	330	0.9%

Han

Value	Count	Frequency (%)
的	1	20.0%
者	1	20.0%
舞	1	20.0%
后	1	20.0%
最	1	20.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	166188	> 99.9%
Punctuation	39	< 0.1%
CJK	5	< 0.1%
None	2	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	26926	16.2%
e	17450	10.5%
o	10463	6.3%
t	10358	6.2%
a	8761	5.3%
n	8406	5.1%
i	8137	4.9%
r	7933	4.8%
s	7648	4.6%
h	6587	4.0%
Other values (72)	53519	32.2%

Punctuation

Value	Count	Frequency (%)
’	28	71.8%
…	10	25.6%
–	1	2.6%

None

Value	Count	Frequency (%)
é	1	50.0%
á	1	50.0%

CJK

Value	Count	Frequency (%)
的	1	20.0%
者	1	20.0%
舞	1	20.0%
后	1	20.0%
最	1	20.0%

title
Categorical

HIGH CARDINALITY UNIFORM

Distinct	4800
Distinct (%)	99.9%
Missing	0
Missing (%)	0.0%
Memory size	37.6 KiB

The Host	2
Batman	2
Out of the Blue	2
Avatar	1
The Girl on the Train	1
Other values (4795)	4795

Length

Max length	86
Median length	58
Mean length	15.349157
Min length	1

Characters and Unicode

Total characters	73722
Distinct characters	98
Distinct categories	14 ?
Distinct scripts	2 ?
Distinct blocks	4 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4797 ?
Unique (%)	99.9%

Sample

1st row	Avatar
2nd row	Pirates of the Caribbean: At World's End
3rd row	Spectre
4th row	The Dark Knight Rises
5th row	John Carter

Common Values

Value	Count	Frequency (%)
The Host	2	< 0.1%
Batman	2	< 0.1%
Out of the Blue	2	< 0.1%
Avatar	1	< 0.1%
The Girl on the Train	1	< 0.1%
Polisse	1	< 0.1%
Beneath Hill 60	1	< 0.1%
The I Inside	1	< 0.1%
Ultramarines: A Warhammer 40,000 Movie	1	< 0.1%
Crocodile Dundee	1	< 0.1%
Other values (4790)	4790	99.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
the	1526	11.4%
of	474	3.5%
a	180	1.3%
and	139	1.0%
in	116	0.9%
to	107	0.8%
2	103	0.8%
	79	0.6%
man	66	0.5%
love	56	0.4%
Other values (4810)	10508	78.7%

Most occurring characters

Value	Count	Frequency (%)
	8553	11.6%
e	7525	10.2%
a	4632	6.3%
o	4470	6.1%
n	3950	5.4%
r	3946	5.4%
i	3765	5.1%
t	3660	5.0%
s	2862	3.9%
h	2852	3.9%
Other values (88)	27507	37.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	51907	70.4%
Uppercase Letter	11748	15.9%
Space Separator	8553	11.6%
Other Punctuation	909	1.2%
Decimal Number	494	0.7%
Dash Punctuation	82	0.1%
Open Punctuation	7	< 0.1%
Close Punctuation	7	< 0.1%
Currency Symbol	4	< 0.1%
Other Number	4	< 0.1%
Other values (4)	7	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	7525	14.5%
a	4632	8.9%
o	4470	8.6%
n	3950	7.6%
r	3946	7.6%
i	3765	7.3%
t	3660	7.1%
s	2862	5.5%
h	2852	5.5%
l	2417	4.7%
Other values (23)	11828	22.8%

Uppercase Letter

Value	Count	Frequency (%)
T	1668	14.2%
S	1007	8.6%
M	800	6.8%
B	756	6.4%
D	687	5.8%
C	663	5.6%
A	640	5.4%
L	543	4.6%
H	541	4.6%
W	500	4.3%
Other values (17)	3943	33.6%

Other Punctuation

Value	Count	Frequency (%)
:	351	38.6%
'	221	24.3%
.	141	15.5%
,	75	8.3%
&	61	6.7%
!	31	3.4%
?	17	1.9%
/	7	0.8%
*	2	0.2%
#	2	0.2%

Decimal Number

Value	Count	Frequency (%)
2	146	29.6%
1	79	16.0%
0	77	15.6%
3	72	14.6%
4	33	6.7%
5	21	4.3%
8	21	4.3%
9	16	3.2%
7	15	3.0%
6	14	2.8%

Other Number

Value	Count	Frequency (%)
½	1	25.0%
³	1	25.0%
²	1	25.0%
⅓	1	25.0%

Dash Punctuation

Value	Count	Frequency (%)
-	80	97.6%
–	2	2.4%

Open Punctuation

Value	Count	Frequency (%)
(	5	71.4%
[	2	28.6%

Close Punctuation

Value	Count	Frequency (%)
)	5	71.4%
]	2	28.6%

Currency Symbol

Value	Count	Frequency (%)
¢	2	50.0%
$	2	50.0%

Space Separator

Value	Count	Frequency (%)
	8553	100.0%

Final Punctuation

Value	Count	Frequency (%)
’	3	100.0%

Math Symbol

Value	Count	Frequency (%)
+	2	100.0%

Other Symbol

Value	Count	Frequency (%)
°	1	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	63655	86.3%
Common	10067	13.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	7525	11.8%
a	4632	7.3%
o	4470	7.0%
n	3950	6.2%
r	3946	6.2%
i	3765	5.9%
t	3660	5.7%
s	2862	4.5%
h	2852	4.5%
l	2417	3.8%
Other values (50)	23576	37.0%

Common

Value	Count	Frequency (%)
	8553	85.0%
:	351	3.5%
'	221	2.2%
2	146	1.5%
.	141	1.4%
-	80	0.8%
1	79	0.8%
0	77	0.8%
,	75	0.7%
3	72	0.7%
Other values (28)	272	2.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	73696	> 99.9%
None	20	< 0.1%
Punctuation	5	< 0.1%
Number Forms	1	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	8553	11.6%
e	7525	10.2%
a	4632	6.3%
o	4470	6.1%
n	3950	5.4%
r	3946	5.4%
i	3765	5.1%
t	3660	5.0%
s	2862	3.9%
h	2852	3.9%
Other values (71)	27481	37.3%

None

Value	Count	Frequency (%)
é	6	30.0%
¢	2	10.0%
Æ	1	5.0%
ë	1	5.0%
½	1	5.0%
à	1	5.0%
·	1	5.0%
ü	1	5.0%
³	1	5.0%
á	1	5.0%
Other values (4)	4	20.0%

Punctuation

Value	Count	Frequency (%)
’	3	60.0%
–	2	40.0%

Number Forms

Value	Count	Frequency (%)
⅓	1	100.0%

vote_average
Real number (ℝ)

Distinct	71
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.0921716

Minimum	0
Maximum	10
Zeros	63
Zeros (%)	1.3%
Negative	0
Negative (%)	0.0%
Memory size	37.6 KiB

Quantile statistics

Minimum	0
5-th percentile	4.3
Q1	5.6
median	6.2
Q3	6.8
95-th percentile	7.6
Maximum	10
Range	10
Interquartile range (IQR)	1.2

Descriptive statistics

Standard deviation	1.1946122
Coefficient of variation (CV)	0.19608971
Kurtosis	7.7923628
Mean	6.0921716
Median Absolute Deviation (MAD)	0.6
Skewness	-1.95971
Sum	29260.7
Variance	1.4270982
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
6.5	216	4.5%
6	216	4.5%
6.7	213	4.4%
6.3	207	4.3%
6.1	201	4.2%
6.4	201	4.2%
6.2	200	4.2%
6.6	198	4.1%
5.9	196	4.1%
5.8	187	3.9%
Other values (61)	2768	57.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	63	1.3%
0.5	1	< 0.1%
1	2	< 0.1%
1.9	1	< 0.1%
2	6	0.1%
2.2	1	< 0.1%
2.3	2	< 0.1%
2.4	1	< 0.1%
2.6	1	< 0.1%
2.7	1	< 0.1%

Value	Count	Frequency (%)
10	4	0.1%
9.5	1	< 0.1%
9.3	1	< 0.1%
8.5	2	< 0.1%
8.4	2	< 0.1%
8.3	7	0.1%
8.2	15	0.3%
8.1	18	0.4%
8	35	0.7%
7.9	32	0.7%

vote_count
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	1609
Distinct (%)	33.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	690.21799

Minimum	0
Maximum	13752
Zeros	62
Zeros (%)	1.3%
Negative	0
Negative (%)	0.0%
Memory size	37.6 KiB

Quantile statistics

Minimum	0
5-th percentile	4
Q1	54
median	235
Q3	737
95-th percentile	3040.9
Maximum	13752
Range	13752
Interquartile range (IQR)	683

Descriptive statistics

Standard deviation	1234.5859
Coefficient of variation (CV)	1.7886898
Kurtosis	19.913946
Mean	690.21799
Median Absolute Deviation (MAD)	214
Skewness	3.8240685
Sum	3315117
Variance	1524202.3
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	62	1.3%
1	53	1.1%
2	46	1.0%
4	43	0.9%
3	41	0.9%
6	38	0.8%
8	37	0.8%
10	34	0.7%
11	32	0.7%
9	32	0.7%
Other values (1599)	4385	91.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	62	1.3%
1	53	1.1%
2	46	1.0%
3	41	0.9%
4	43	0.9%
5	28	0.6%
6	38	0.8%
7	31	0.6%
8	37	0.8%
9	32	0.7%

Value	Count	Frequency (%)
13752	1	< 0.1%
12002	1	< 0.1%
11800	1	< 0.1%
11776	1	< 0.1%
10995	1	< 0.1%
10867	1	< 0.1%
10099	1	< 0.1%
9742	1	< 0.1%
9455	1	< 0.1%
9427	1	< 0.1%

cast
Categorical

HIGH CARDINALITY UNIFORM

Distinct	4741
Distinct (%)	99.6%
Missing	43
Missing (%)	0.9%
Memory size	37.6 KiB

William Shatner Leonard Nimoy DeForest Kelley James Doohan George Takei	6
Patrick Stewart Jonathan Frakes Brent Spiner LeVar Burton Michael Dorn	4
Jennifer Lawrence Josh Hutcherson Liam Hemsworth Woody Harrelson Elizabeth Banks	3
Zac Efron Vanessa Hudgens Ashley Tisdale Lucas Grabeel Corbin Bleu	3
Elijah Wood Ian McKellen Viggo Mortensen Liv Tyler Orlando Bloom	2
Other values (4736)	4742

Length

Max length	132
Median length	99
Mean length	69.596429
Min length	7

Characters and Unicode

Total characters	331279
Distinct characters	69
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4730 ?
Unique (%)	99.4%

Sample

1st row	Sam Worthington Zoe Saldana Sigourney Weaver Stephen Lang Michelle Rodriguez
2nd row	Johnny Depp Orlando Bloom Keira Knightley Stellan Skarsg\u00e5rd Chow Yun-fat
3rd row	Daniel Craig Christoph Waltz L\u00e9a Seydoux Ralph Fiennes Monica Bellucci
4th row	Christian Bale Michael Caine Gary Oldman Anne Hathaway Tom Hardy
5th row	Taylor Kitsch Lynn Collins Samantha Morton Willem Dafoe Thomas Haden Church

Common Values

Value	Count	Frequency (%)
William Shatner Leonard Nimoy DeForest Kelley James Doohan George Takei	6	0.1%
Patrick Stewart Jonathan Frakes Brent Spiner LeVar Burton Michael Dorn	4	0.1%
Jennifer Lawrence Josh Hutcherson Liam Hemsworth Woody Harrelson Elizabeth Banks	3	0.1%
Zac Efron Vanessa Hudgens Ashley Tisdale Lucas Grabeel Corbin Bleu	3	0.1%
Elijah Wood Ian McKellen Viggo Mortensen Liv Tyler Orlando Bloom	2	< 0.1%
Eddie Murphy Judge Reinhold John Ashton Ronny Cox Paul Reiser	2	< 0.1%
Ewan McGregor Natalie Portman Hayden Christensen Ian McDiarmid Samuel L. Jackson	2	< 0.1%
Martin Freeman Ian McKellen Richard Armitage Ken Stott Graham McTavish	2	< 0.1%
Patrick Stewart Hugh Jackman Ian McKellen Halle Berry Famke Janssen	2	< 0.1%
Mark Hamill Harrison Ford Carrie Fisher Billy Dee Williams Anthony Daniels	2	< 0.1%
Other values (4731)	4732	98.5%
(Missing)	43	0.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
michael	432	0.9%
john	430	0.9%
james	327	0.7%
david	282	0.6%
robert	260	0.5%
jason	209	0.4%
tom	196	0.4%
paul	195	0.4%
kevin	183	0.4%
chris	169	0.3%
Other values (9434)	46055	94.5%

Most occurring characters

Value	Count	Frequency (%)
	43994	13.3%
e	29691	9.0%
a	27740	8.4%
n	22662	6.8%
r	19487	5.9%
i	19078	5.8%
o	17050	5.1%
l	15752	4.8%
t	11035	3.3%
s	10981	3.3%
Other values (59)	113809	34.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	233500	70.5%
Uppercase Letter	49836	15.0%
Space Separator	43994	13.3%
Decimal Number	2063	0.6%
Other Punctuation	1528	0.5%
Dash Punctuation	358	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	29691	12.7%
a	27740	11.9%
n	22662	9.7%
r	19487	8.3%
i	19078	8.2%
o	17050	7.3%
l	15752	6.7%
t	11035	4.7%
s	10981	4.7%
h	8907	3.8%
Other values (16)	51117	21.9%

Uppercase Letter

Value	Count	Frequency (%)
M	4328	8.7%
J	4181	8.4%
S	3849	7.7%
C	3836	7.7%
B	3668	7.4%
D	3090	6.2%
R	2929	5.9%
A	2765	5.5%
L	2407	4.8%
H	2332	4.7%
Other values (16)	16451	33.0%

Decimal Number

Value	Count	Frequency (%)
0	1387	67.2%
9	250	12.1%
1	172	8.3%
4	61	3.0%
3	45	2.2%
5	42	2.0%
7	32	1.6%
6	32	1.6%
8	30	1.5%
2	12	0.6%

Other Punctuation

Value	Count	Frequency (%)
\	723	47.3%
.	600	39.3%
'	188	12.3%
,	11	0.7%
"	6	0.4%

Space Separator

Value	Count	Frequency (%)
	43994	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	358	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	283336	85.5%
Common	47943	14.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	29691	10.5%
a	27740	9.8%
n	22662	8.0%
r	19487	6.9%
i	19078	6.7%
o	17050	6.0%
l	15752	5.6%
t	11035	3.9%
s	10981	3.9%
h	8907	3.1%
Other values (42)	100953	35.6%

Common

Value	Count	Frequency (%)
	43994	91.8%
0	1387	2.9%
\	723	1.5%
.	600	1.3%
-	358	0.7%
9	250	0.5%
'	188	0.4%
1	172	0.4%
4	61	0.1%
3	45	0.1%
Other values (7)	165	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	331279	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	43994	13.3%
e	29691	9.0%
a	27740	8.4%
n	22662	6.8%
r	19487	5.9%
i	19078	5.8%
o	17050	5.1%
l	15752	4.8%
t	11035	3.3%
s	10981	3.3%
Other values (59)	113809	34.4%

crew
Categorical

HIGH CARDINALITY UNIFORM

Distinct	4776
Distinct (%)	99.4%
Missing	0
Missing (%)	0.0%
Memory size	37.6 KiB

[]	28
[{'name': 'Stephen E. 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Hernandez', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Set Costumer', 'credit_id': '54959ff9c3a3686ae300440c', 'id': 1401814}, {'name': 'Marvin Hall', 'gender': 0, 'department': 'Editing', 'job': 'Digital Intermediate', 'credit_id': '5495a0ddc3a3686ae10046fe', 'id': 1401815}, {'name': 'Judy Alley', 'gender': 0, 'department': 'Production', 'job': 'Publicist', 'credit_id': '5495a1f7c3a3686ae3004443', 'id': 1401816}, {'name': 'Mike Perry', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b29fc3a36869d100002f', 'id': 1418381}, {'name': 'Andrew Morley', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b23a9251415df8001081', 'id': 1426854}, {'name': 'Seth Engstrom', 'gender': 0, 'department': 'Art', 'job': 'Conceptual Design', 'credit_id': '55491e1192514104c40002d8', 'id': 1438901}, {'name': 'Eric Oliver', 'gender': 0, 'department': 'Crew', 'job': 'Visual Effects Art Director', 'credit_id': '5525d5809251417276002b06', 'id': 1447362}, {'name': 'Matsune Suzuki', 'gender': 0, 'department': 'Visual Effects', 'job': 'Modeling', 'credit_id': '554427ca925141586500312a', 'id': 1447503}, {'name': 'Paul Tobin', 'gender': 0, 'department': 'Art', 'job': 'Art Department Manager', 'credit_id': '551906889251415aab001c88', 'id': 1447524}, {'name': 'Roxane Griffin', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Hairstylist', 'credit_id': '5592af8492514152cc0010de', 'id': 1452643}, {'name': 'Arun Ram-Mohan', 'gender': 0, 'department': 'Lighting', 'job': 'Lighting Artist', 'credit_id': '553d3c109251415852001318', 'id': 1453938}, {'name': 'Georgia Lockhart-Adams', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '5592af4692514152d5001355', 'id': 1457305}, {'name': 'Thrain Shadbolt', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b2eac3a36877470012a5', 'id': 1466035}, {'name': 'Brad Alexander', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b032c3a36877450015f1', 'id': 1483220}, {'name': 'Shadi Almassizadeh', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b05592514152d80012f6', 'id': 1483221}, {'name': 'Simon Clutterbuck', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b090c3a36877570010b5', 'id': 1483222}, {'name': 'Graeme Demmocks', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b0dbc3a368774b00112c', 'id': 1483223}, {'name': 'Adrian Fernandes', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b0fe92514152db0010c1', 'id': 1483224}, {'name': 'Mitch Gates', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b11f9251415df8001059', 'id': 1483225}, {'name': 'Jerry Kung', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b15dc3a3687745001645', 'id': 1483226}, {'name': 'Andy Lomas', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b18e925141645a0004ae', 'id': 1483227}, {'name': 'Sebastian Marino', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b1bfc3a368775d0010e7', 'id': 1483228}, {'name': 'Matthias Menz', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b2049251415df8001078', 'id': 1483229}, {'name': 'Sergei Nevshupov', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b27b92514152d800136a', 'id': 1483230}, {'name': 'Philippe Rebours', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b2c3c3a36869e800003c', 'id': 1483231}, {'name': 'Michael Takarangi', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b317c3a36877470012af', 'id': 1483232}, {'name': 'David Weitzberg', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b345c3a36877470012bb', 'id': 1483233}, {'name': 'Ben White', 'gender': 0, 'department': 'Crew', 'job': 'CG Supervisor', 'credit_id': '5592b37cc3a368775100113b', 'id': 1483234}, {'name': 'Min Windle', 'gender': 1, 'department': 'Crew', 'job': 'Stunts', 'credit_id': '573c8e2f9251413f5d000094', 'id': 1621932}]	1
[{'name': 'William M. Anderson', 'gender': 2, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe451bc3a36847f80bcdd1', 'id': 2705}, {'name': 'David Rubin', 'gender': 2, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '52fe451bc3a36847f80bcdad', 'id': 5490}, {'name': 'Marco Weber', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe451bc3a36847f80bcdbf', 'id': 15366}, {'name': 'Wedigo von Schultzendorff', 'gender': 2, 'department': 'Camera', 'job': 'Director of Photography', 'credit_id': '52fe451bc3a36847f80bcdcb', 'id': 15367}, {'name': 'Lee Solomon', 'gender': 0, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '52fe451bc3a36847f80bcdb3', 'id': 32344}, {'name': 'Padraic McKinley', 'gender': 0, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe451bc3a36847f80bcddd', 'id': 36619}, {'name': 'Burr Steers', 'gender': 0, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe451bc3a36847f80bcd9b', 'id': 58552}, {'name': 'Burr Steers', 'gender': 0, 'department': 'Writing', 'job': 'Author', 'credit_id': '52fe451bc3a36847f80bcde3', 'id': 58552}, {'name': 'Helen Beadleston', 'gender': 1, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '52fe451bc3a36847f80bcda1', 'id': 65845}, {'name': 'Fran Lucci', 'gender': 0, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '52fe451bc3a36847f80bcda7', 'id': 65846}, {'name': 'Lisa Tornell', 'gender': 1, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe451bc3a36847f80bcdb9', 'id': 65847}, {'name': 'J\\u00f6rn-Uwe Fahrenkrog-Petersen', 'gender': 0, 'department': 'Sound', 'job': 'Music', 'credit_id': '52fe451bc3a36847f80bcdc5', 'id': 65848}, {'name': 'Robert Frazen', 'gender': 2, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe451bc3a36847f80bcdd7', 'id': 65849}]	1
[{'name': 'Carter Burwell', 'gender': 2, 'department': 'Sound', 'job': 'Original Music Composer', 'credit_id': '52fe4316c3a36847f803946d', 'id': 1225}, {'name': 'Susie Figgis', 'gender': 1, 'department': 'Production', 'job': 'Casting', 'credit_id': '52fe4316c3a36847f8039479', 'id': 1302}, {'name': 'Bob Weinstein', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4316c3a36847f8039467', 'id': 1307}, {'name': 'Harvey Weinstein', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4316c3a36847f8039461', 'id': 59839}, {'name': 'Dan Korintus', 'gender': 2, 'department': 'Editing', 'job': 'Dialogue Editor', 'credit_id': '56452a9fc3a36870e3007459', 'id': 5337}, {'name': 'Sandy Powell', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Costume Design', 'credit_id': '52fe4316c3a36847f803949f', 'id': 9027}, {'name': 'Todd Haynes', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe4316c3a36847f803945b', 'id': 16863}, {'name': 'Todd Haynes', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '56452a1dc3a36870ec00690d', 'id': 16863}, {'name': 'Todd Haynes', 'gender': 2, 'department': 'Writing', 'job': 'Story', 'credit_id': '56452a259251410a47006d52', 'id': 16863}, {'name': 'James Lyons', 'gender': 2, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe4316c3a36847f8039473', 'id': 17234}, {'name': 'James Lyons', 'gender': 2, 'department': 'Writing', 'job': 'Story', 'credit_id': '56452a31c3a36870d6006ebd', 'id': 17234}, {'name': 'Todd Kasow', 'gender': 0, 'department': 'Sound', 'job': 'Music Editor', 'credit_id': '564528f7c3a36870d6006e56', 'id': 17990}, {'name': 'Maryse Alberti', 'gender': 1, 'department': 'Camera', 'job': 'Director of Photography', 'credit_id': '52fe4316c3a36847f803947f', 'id': 33678}, {'name': 'Randall Poster', 'gender': 2, 'department': 'Sound', 'job': 'Music Supervisor', 'credit_id': '564528ab9251410a3f006b1c', 'id': 52161}, {'name': 'Christopher Hobbs', 'gender': 0, 'department': 'Art', 'job': 'Production Design', 'credit_id': '56452912c3a36870ef006dad', 'id': 206531}, {'name': 'Annette Kudrak', 'gender': 0, 'department': 'Sound', 'job': 'Music Editor', 'credit_id': '564528e99251410a47006cfa', 'id': 1427381}, {'name': 'June McDonald', 'gender': 0, 'department': 'Directing', 'job': 'Script Supervisor', 'credit_id': '564528dbc3a36870ef006d9b', 'id': 1535092}]	1
[{'name': 'Aaron Ryder', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe45099251416c75049843', 'id': 554}, {'name': 'Albert Berger', 'gender': 2, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '52fe45099251416c75049855', 'id': 17172}, {'name': 'Ron Yerxa', 'gender': 2, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '52fe45099251416c7504985b', 'id': 17173}, {'name': 'Jeff Freeman', 'gender': 2, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe45099251416c7504986d', 'id': 11876}, {'name': 'Pam Dixon', 'gender': 1, 'department': 'Production', 'job': 'Casting', 'credit_id': '52fe45099251416c75049873', 'id': 18457}, {'name': 'Alexander Gruszynski', 'gender': 2, 'department': 'Camera', 'job': 'Director of Photography', 'credit_id': '52fe45099251416c75049867', 'id': 33651}, {'name': 'Pam Brady', 'gender': 1, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '52fe45099251416c750497fb', 'id': 34522}, {'name': 'Andrew Fleming', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe45099251416c750497ef', 'id': 41549}, {'name': 'Andrew Fleming', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '52fe45099251416c750497f5', 'id': 41549}, {'name': 'Eric Eisner', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe45099251416c7504983d', 'id': 73135}, {'name': 'Leonid Rozhetskin', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe45099251416c75049849', 'id': 73136}, {'name': 'Ralph Sall', 'gender': 2, 'department': 'Sound', 'job': 'Original Music Composer', 'credit_id': '52fe45099251416c75049861', 'id': 73137}, {'name': 'Michael Flynn', 'gender': 0, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '55a6d74c9251411e060004f3', 'id': 1382732}]	1
Other values (4771)	4771

Length

Max length	62973
Median length	7586
Mean length	3955.6288
Min length	2

Characters and Unicode

Total characters	18998885
Distinct characters	80
Distinct categories	10 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4775 ?
Unique (%)	99.4%

Sample

1st row	[{'name': 'Stephen E. Rivkin', 'gender': 0, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe48009251416c750aca23', 'id': 1721}, {'name': 'Rick Carter', 'gender': 2, 'department': 'Art', 'job': 'Production Design', 'credit_id': '539c47ecc3a36810e3001f87', 'id': 496}, {'name': 'Christopher Boyes', 'gender': 0, 'department': 'Sound', 'job': 'Sound Designer', 'credit_id': '54491c89c3a3680fb4001cf7', 'id': 900}, {'name': 'Christopher Boyes', 'gender': 0, 'department': 'Sound', 'job': 'Supervising Sound Editor', 'credit_id': '54491cb70e0a267480001bd0', 'id': 900}, {'name': 'Mali Finn', 'gender': 1, 'department': 'Production', 'job': 'Casting', 'credit_id': '539c4a4cc3a36810c9002101', 'id': 1262}, {'name': 'James Horner', 'gender': 2, 'department': 'Sound', 'job': 'Original Music Composer', 'credit_id': '5544ee3b925141499f0008fc', 'id': 1729}, {'name': 'James Cameron', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe48009251416c750ac9c3', 'id': 2710}, {'name': 'James Cameron', 'gender': 2, 'department': 'Writing', 'job': 'Writer', 'credit_id': '52fe48009251416c750ac9d9', 'id': 2710}, {'name': 'James Cameron', 'gender': 2, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe48009251416c750aca17', 'id': 2710}, {'name': 'James Cameron', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe48009251416c750aca29', 'id': 2710}, {'name': 'James Cameron', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '52fe48009251416c750aca3f', 'id': 2710}, {'name': 'Andrew Menzies', 'gender': 2, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '539c4987c3a36810ba0021a4', 'id': 7236}, {'name': 'Jill Brooks', 'gender': 0, 'department': 'Visual Effects', 'job': 'Visual Effects Producer', 'credit_id': '549598c3c3a3686ae9004383', 'id': 6690}, {'name': 'Margery Simkin', 'gender': 1, 'department': 'Production', 'job': 'Casting', 'credit_id': '52fe48009251416c750aca4b', 'id': 6347}, {'name': 'Kevin Ishioka', 'gender': 2, 'department': 'Art', 'job': 'Supervising Art Director', 'credit_id': '570b6f419251417da70032fe', 'id': 6878}, {'name': 'Dick Bernstein', 'gender': 0, 'department': 'Sound', 'job': 'Music Editor', 'credit_id': '5495a0fac3a3686ae9004468', 'id': 6883}, {'name': 'Shannon Mills', 'gender': 0, 'department': 'Sound', 'job': 'Sound Effects Editor', 'credit_id': '54959706c3a3686af3003e81', 'id': 8159}, {'name': 'Dennie Thorpe', 'gender': 0, 'department': 'Sound', 'job': 'Foley', 'credit_id': '54491d58c3a3680fb1001ccb', 'id': 8160}, {'name': 'Jana Vance', 'gender': 0, 'department': 'Sound', 'job': 'Foley', 'credit_id': '54491d6cc3a3680fa5001b2c', 'id': 8163}, {'name': 'Deborah Lynn Scott', 'gender': 1, 'department': 'Costume & Make-Up', 'job': 'Costume Design', 'credit_id': '52fe48009251416c750aca57', 'id': 8527}, {'name': 'Jon Landau', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe48009251416c750aca2f', 'id': 8529}, {'name': 'Sean Haworth', 'gender': 0, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '539c4937c3a36810ba002194', 'id': 9618}, {'name': 'Kim Sinclair', 'gender': 1, 'department': 'Art', 'job': 'Set Decoration', 'credit_id': '539c49b6c3a36810c10020e6', 'id': 12653}, {'name': 'Kim Sinclair', 'gender': 1, 'department': 'Art', 'job': 'Supervising Art Director', 'credit_id': '570b6f2f9251413a0e00020d', 'id': 12653}, {'name': 'Richard F. Mays', 'gender': 2, 'department': 'Art', 'job': 'Set Designer', 'credit_id': '54491a6c0e0a26748c001b19', 'id': 14350}, {'name': 'Laeta Kalogridis', 'gender': 1, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '56928cf4c3a3684cff0025c4', 'id': 20294}, {'name': 'Mayes C. 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2nd row	[{'name': 'Dariusz Wolski', 'gender': 2, 'department': 'Camera', 'job': 'Director of Photography', 'credit_id': '52fe4232c3a36847f800b579', 'id': 120}, {'name': 'Gore Verbinski', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe4232c3a36847f800b4fd', 'id': 1704}, {'name': 'Jerry Bruckheimer', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4232c3a36847f800b54f', 'id': 770}, {'name': 'Ted Elliott', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '52fe4232c3a36847f800b503', 'id': 1705}, {'name': 'Terry Rossio', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '52fe4232c3a36847f800b509', 'id': 1706}, {'name': 'Stephen E. Rivkin', 'gender': 0, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe4232c3a36847f800b57f', 'id': 1721}, {'name': 'Craig Wood', 'gender': 2, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe4232c3a36847f800b585', 'id': 1722}, {'name': 'Hans Zimmer', 'gender': 2, 'department': 'Sound', 'job': 'Original Music Composer', 'credit_id': '52fe4232c3a36847f800b573', 'id': 947}, {'name': 'Mike Stenson', 'gender': 2, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '52fe4232c3a36847f800b555', 'id': 2444}, {'name': 'Eric McLeod', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4232c3a36847f800b561', 'id': 2445}, {'name': 'Chad Oman', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4232c3a36847f800b55b', 'id': 2446}, {'name': 'Peter Kohn', 'gender': 0, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4232c3a36847f800b567', 'id': 2447}, {'name': 'Pat Sandston', 'gender': 0, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4232c3a36847f800b56d', 'id': 2448}, {'name': 'Denise Chamian', 'gender': 1, 'department': 'Production', 'job': 'Casting', 'credit_id': '52fe4232c3a36847f800b58b', 'id': 2215}, {'name': 'Rick Heinrichs', 'gender': 2, 'department': 'Art', 'job': 'Production Design', 'credit_id': '52fe4232c3a36847f800b597', 'id': 1226}, {'name': 'John Dexter', 'gender': 2, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '52fe4232c3a36847f800b59d', 'id': 553}, {'name': 'Priscilla John', 'gender': 1, 'department': 'Production', 'job': 'Casting', 'credit_id': '52fe4232c3a36847f800b591', 'id': 3311}, {'name': 'Cheryl Carasik', 'gender': 1, 'department': 'Art', 'job': 'Set Decoration', 'credit_id': '52fe4232c3a36847f800b5a3', 'id': 4032}, {'name': 'Liz Dann', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Costume Design', 'credit_id': '52fe4232c3a36847f800b5a9', 'id': 4033}, {'name': 'Penny Rose', 'gender': 1, 'department': 'Costume & Make-Up', 'job': 'Costume Design', 'credit_id': '52fe4232c3a36847f800b5af', 'id': 4034}, {'name': 'Bob Badami', 'gender': 2, 'department': 'Sound', 'job': 'Music Supervisor', 'credit_id': '56427ce8c3a3686a53000d8b', 'id': 5132}, {'name': 'James Ward Byrkit', 'gender': 2, 'department': 'Art', 'job': 'Conceptual Design', 'credit_id': '55993c15c3a36855db002f33', 'id': 146439}, {'name': 'Ve Neill', 'gender': 1, 'department': 'Costume & Make-Up', 'job': 'Makeup Department Head', 'credit_id': '52fe4232c3a36847f800b5b9', 'id': 406204}, {'name': 'John Dixon', 'gender': 2, 'department': 'Crew', 'job': 'Stunts', 'credit_id': '56e47f7892514132690017bd', 'id': 1259516}, {'name': 'Dottie Starling', 'gender': 0, 'department': 'Crew', 'job': 'CGI Supervisor', 'credit_id': '5740be639251416597000849', 'id': 1336716}, {'name': 'Pamela Alch', 'gender': 1, 'department': 'Directing', 'job': 'Script Supervisor', 'credit_id': '56427c639251412fc8000dc1', 'id': 1344278}, {'name': 'Allen Hall', 'gender': 0, 'department': 'Crew', 'job': 'Special Effects Coordinator', 'credit_id': '57083101c3a3681d320004e6', 'id': 1368867}, {'name': 'Melissa Muik', 'gender': 0, 'department': 'Sound', 'job': 'Music Editor', 'credit_id': '56427d5ec3a3686a62000d4a', 'id': 1368884}, {'name': 'Sharron Reynolds', 'gender': 1, 'department': 'Directing', 'job': 'Script Supervisor', 'credit_id': '56427c7b9251412fd4000e07', 'id': 1395290}, {'name': 'Barbara McDermott', 'gender': 0, 'department': 'Sound', 'job': 'Music Editor', 'credit_id': '56427d2bc3a3686a53000d9b', 'id': 1399327}, {'name': 'Karen Golden', 'gender': 1, 'department': 'Directing', 'job': 'Script Supervisor', 'credit_id': '56427cb4c3a3686a53000d87', 'id': 1400738}, {'name': 'Katie Greathouse', 'gender': 0, 'department': 'Sound', 'job': 'Music Editor', 'credit_id': '56427d169251412fd4000e23', 'id': 1534197}]
3rd row	[{'name': 'Thomas Newman', 'gender': 2, 'department': 'Sound', 'job': 'Original Music Composer', 'credit_id': '54805967c3a36829b5002c41', 'id': 153}, {'name': 'Sam Mendes', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe4d22c3a368484e1d8d77', 'id': 39}, {'name': 'Anna Pinnock', 'gender': 1, 'department': 'Art', 'job': 'Set Decoration', 'credit_id': '5677cd99925141691a005333', 'id': 8384}, {'name': 'John Logan', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '52fe4d22c3a368484e1d8d8d', 'id': 932}, {'name': 'John Logan', 'gender': 2, 'department': 'Writing', 'job': 'Story', 'credit_id': '562fc9bb92514129fe0006b4', 'id': 932}, {'name': 'Dennis Gassner', 'gender': 2, 'department': 'Art', 'job': 'Production Design', 'credit_id': '5654d41c92514145c3000373', 'id': 4248}, {'name': 'Ian Fleming', 'gender': 2, 'department': 'Writing', 'job': 'Characters', 'credit_id': '52fe4d22c3a368484e1d8d71', 'id': 9856}, {'name': 'Lee Smith', 'gender': 0, 'department': 'Editing', 'job': 'Editor', 'credit_id': '54805989c3a36829ae0022d8', 'id': 3904}, {'name': 'Bill Bernstein', 'gender': 2, 'department': 'Sound', 'job': 'Music Editor', 'credit_id': '5677df82c3a3681683008748', 'id': 7538}, {'name': 'Daniel Craig', 'gender': 2, 'department': 'Production', 'job': 'Co-Producer', 'credit_id': '5720e370c3a368117e00045b', 'id': 8784}, {'name': 'Jany Temime', 'gender': 1, 'department': 'Costume & Make-Up', 'job': 'Costume Design', 'credit_id': '5522fdd09251416d4a0024b6', 'id': 11227}, {'name': 'Debbie McWilliams', 'gender': 1, 'department': 'Production', 'job': 'Casting', 'credit_id': '5677cc9ac3a368167c0089b5', 'id': 10496}, {'name': 'Barbara Broccoli', 'gender': 1, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4d22c3a368484e1d8d7d', 'id': 10666}, {'name': 'Roberto Malerba', 'gender': 0, 'department': 'Production', 'job': 'Line Producer', 'credit_id': '5720e3afc3a368117e00046a', 'id': 11268}, {'name': 'Peter Clarke', 'gender': 0, 'department': 'Sound', 'job': 'Music Editor', 'credit_id': '5677df58c3a368167c008c82', 'id': 40827}, {'name': 'Christopher Assells', 'gender': 0, 'department': 'Sound', 'job': 'Sound Designer', 'credit_id': '5677dd1ec3a36816890085d3', 'id': 14764}, {'name': 'Per Hallberg', 'gender': 0, 'department': 'Sound', 'job': 'Supervising Sound Editor', 'credit_id': '566046b9c3a36875f400323a', 'id': 14765}, {'name': 'Nicole Schmied', 'gender': 0, 'department': 'Production', 'job': 'Casting', 'credit_id': '5677ccab925141691a00530f', 'id': 36108}, {'name': 'Nicole Schmied', 'gender': 0, 'department': 'Production', 'job': 'Casting Associate', 'credit_id': '5677cfe4c3a36816850087d2', 'id': 36108}, {'name': 'Robert Wade', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '562fc984c3a3681b5400e16f', 'id': 10783}, {'name': 'Robert Wade', 'gender': 2, 'department': 'Writing', 'job': 'Story', 'credit_id': '562fc9cec3a3681b4b00d168', 'id': 10783}, {'name': 'Neal Purvis', 'gender': 0, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '562fc976c3a3681b5c00dd64', 'id': 10782}, {'name': 'Neal Purvis', 'gender': 0, 'department': 'Writing', 'job': 'Story', 'credit_id': '562fc9d79251414ad800c103', 'id': 10782}, {'name': 'Callum McDougall', 'gender': 2, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '5720e61d9251414235000477', 'id': 10876}, {'name': 'Jez Butterworth', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '562fc9a89251414ad800c0fe', 'id': 21339}, {'name': 'Chris Lowe', 'gender': 0, 'department': 'Art', 'job': 'Supervising Art Director', 'credit_id': '570bd7f2c3a36802a9000412', 'id': 23425}, {'name': 'Roxana Alexandru ', 'gender': 0, 'department': 'Art', 'job': 'Assistant Art Director', 'credit_id': '5677e45ac3a368168b0084fd', 'id': 23491}, {'name': 'Jo Grover', 'gender': 0, 'department': 'Crew', 'job': 'Makeup Effects', 'credit_id': '5677e29c925141691a00561c', 'id': 23774}, {'name': 'St\\u00e9phane Foenkinos', 'gender': 2, 'department': 'Production', 'job': 'Casting', 'credit_id': '5677cf8492514179d20088ae', 'id': 10907}, {'name': 'Lorenzo Senatore', 'gender': 2, 'department': 'Camera', 'job': 'Camera Operator', 'credit_id': '5677d7b192514179d20089c6', 'id': 61851}, {'name': 'Wolfgang Ramml', 'gender': 0, 'department': 'Production', 'job': 'Line Producer', 'credit_id': '5720e6f7925141423000046b', 'id': 64000}, {'name': 'J.A.C. 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Wight', 'gender': 0, 'department': 'Art', 'job': 'Set Designer', 'credit_id': '58c692629251411d620170a7', 'id': 1171098}, {'name': 'Bryan Andrews', 'gender': 0, 'department': 'Art', 'job': 'Storyboard Designer', 'credit_id': '58c692f9c3a36840b8016e22', 'id': 1218986}, {'name': 'Dennis Liddiard', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c6941f9251411d110174ca', 'id': 1316599}, {'name': 'Kevin Haney', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c6943a9251411d0d01804a', 'id': 1319490}, {'name': 'Josh Lusby', 'gender': 0, 'department': 'Art', 'job': 'Assistant Art Director', 'credit_id': '58c69244c3a368413b015a23', 'id': 1334782}, {'name': 'Jamie Wilkinson', 'gender': 0, 'department': 'Art', 'job': 'Property Master', 'credit_id': '58c69ccec3a36841280156f6', 'id': 1335553}, {'name': 'Roger Guyett', 'gender': 0, 'department': 'Crew', 'job': 'Thanks', 'credit_id': '58c69f219251411d190182a8', 'id': 1339450}, {'name': 'Denny Caira', 'gender': 0, 'department': 'Crew', 'job': 'Transportation Coordinator', 'credit_id': '58c69dc79251411d1901819d', 'id': 1357070}, {'name': 'Sue Rowe', 'gender': 0, 'department': 'Visual Effects', 'job': 'Visual Effects Supervisor', 'credit_id': '58c688709251411d3001684b', 'id': 1367497}, {'name': 'Toby Spigel', 'gender': 0, 'department': 'Production', 'job': 'Casting Assistant', 'credit_id': '58c69ca79251411d11017a77', 'id': 1374469}, {'name': 'Marshall Winn', 'gender': 0, 'department': 'Editing', 'job': 'Dialogue Editor', 'credit_id': '58c69aa59251411d11017919', 'id': 1376901}, {'name': 'Michael Semanick', 'gender': 0, 'department': 'Sound', 'job': 'Sound Re-Recording Mixer', 'credit_id': '58c68ee9c3a3684128014e36', 'id': 1378828}, {'name': 'Peter Dorme', 'gender': 0, 'department': 'Art', 'job': 'Assistant Art Director', 'credit_id': '58c692389251411d30016ea2', 'id': 1388850}, {'name': 'Perry Evans', 'gender': 0, 'department': 'Lighting', 'job': 'Gaffer', 'credit_id': '58c69cf49251411d4701890b', 'id': 1390367}, {'name': 'Annie Penn', 'gender': 0, 'department': 'Directing', 'job': 'Script Supervisor', 'credit_id': '58c699f4c3a368413b015f45', 'id': 1390388}, {'name': 'Tim Nielsen', 'gender': 0, 'department': 'Sound', 'job': 'Sound Designer', 'credit_id': '58c69a7ac3a368410c016254', 'id': 1394129}, {'name': 'Tim Nielsen', 'gender': 0, 'department': 'Sound', 'job': 'Supervising Sound Editor', 'credit_id': '58c68edec3a3684114014f16', 'id': 1394129}, {'name': 'Jenne Lee', 'gender': 0, 'department': 'Art', 'job': 'Art Department Coordinator', 'credit_id': '58c6928f9251411d55017337', 'id': 1395430}, {'name': 'Theodore Sharps', 'gender': 0, 'department': 'Art', 'job': 'Set Designer', 'credit_id': '58c6925b9251411d150174df', 'id': 1395435}, {'name': 'Joseph Hodges', 'gender': 0, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '58c691c4c3a36840f6015583', 'id': 1397837}, {'name': 'Philippe Carr-Forster', 'gender': 0, 'department': 'Camera', 'job': 'Camera Operator', 'credit_id': '58c699489251411d300172de', 'id': 1399467}, {'name': 'Christopher Prampin', 'gender': 0, 'department': 'Lighting', 'job': 'Gaffer', 'credit_id': '58c69cfdc3a368413b016165', 'id': 1399475}, {'name': 'Colin Anderson', 'gender': 0, 'department': 'Camera', 'job': 'Camera Operator', 'credit_id': '58c69920c3a36841300154e2', 'id': 1400535}, {'name': 'Colin Anderson', 'gender': 0, 'department': 'Camera', 'job': 'Steadicam Operator', 'credit_id': '58c699259251411d620174e9', 'id': 1400535}, {'name': 'Jennifer Teves', 'gender': 0, 'department': 'Production', 'job': 'Production Supervisor', 'credit_id': '58c699ebc3a368411401561c', 'id': 1401784}, {'name': 'Kim Ayers', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Key Makeup Artist', 'credit_id': '58c6935ec3a368413b015ae4', 'id': 1403388}, {'name': 'Daniel Barrow', 'gender': 0, 'department': 'Visual Effects', 'job': 'Visual Effects Producer', 'credit_id': '58c68e49c3a368413b0157eb', 'id': 1408379}, {'name': 'Debbi Salmon', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Key Makeup Artist', 'credit_id': '58c6936fc3a368413b015aed', 'id': 1409757}, {'name': 'Paula Price', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Key Makeup Artist', 'credit_id': '58c69339c3a36841200154c4', 'id': 1411320}, {'name': 'Frank Connor', 'gender': 0, 'department': 'Camera', 'job': 'Still Photographer', 'credit_id': '58c69dba9251411d0d018767', 'id': 1412205}, {'name': 'J.R. Grubbs', 'gender': 0, 'department': 'Sound', 'job': 'Sound Effects Editor', 'credit_id': '58c69a89c3a3684114015691', 'id': 1414177}, {'name': 'Deborah Rutherford', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c69452c3a36840f6015741', 'id': 1414539}, {'name': 'Don Rutherford', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c6946c9251411d15017617', 'id': 1414540}, {'name': 'Malcolm Fife', 'gender': 0, 'department': 'Sound', 'job': 'Sound Effects Editor', 'credit_id': '58c69a929251411d11017907', 'id': 1415464}, {'name': 'Toby Britton', 'gender': 0, 'department': 'Art', 'job': 'Assistant Art Director', 'credit_id': '58c6923e9251411d11017382', 'id': 1417396}, {'name': 'Kevin Alexander', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Hair Designer', 'credit_id': '58c69866c3a368413001545d', 'id': 1418124}, {'name': 'Kristie Matthiae', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Key Makeup Artist', 'credit_id': '58c693779251411d470181e4', 'id': 1421936}, {'name': 'Gerald Quist', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c694a99251411d15017646', 'id': 1424151}, {'name': 'Nuria Mbomio', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c693f39251411d110174a9', 'id': 1425411}, {'name': 'Eamonn Butler', 'gender': 0, 'department': 'Visual Effects', 'job': 'Animation Supervisor', 'credit_id': '58c68866c3a368413b015367', 'id': 1428901}, {'name': 'Laura Jennings', 'gender': 0, 'department': 'Crew', 'job': 'Visual Effects Editor', 'credit_id': '58c68ec89251411d11017191', 'id': 1428905}, {'name': 'Ailbhe Lemass', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c693919251411d0d017fde', 'id': 1428911}, {'name': 'Simon Finney', 'gender': 0, 'department': 'Camera', 'job': 'Camera Operator', 'credit_id': '58c6992f9251411d19017e49', 'id': 1430188}, {'name': 'Eryn Krueger Mekash', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c6948b9251411d15017628', 'id': 1441176}, {'name': 'Travis Witkowski', 'gender': 0, 'department': 'Art', 'job': 'Art Department Assistant', 'credit_id': '58c692ddc3a368413b015a8d', 'id': 1447571}, {'name': 'Mike Mekash', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c694809251411d15017622', 'id': 1458894}, {'name': 'Kirstin Chalmers', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c6940e9251411d19017aad', 'id': 1530220}, {'name': 'Kacie Seamons', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Key Costumer', 'credit_id': '58c698e89251411d5501777a', 'id': 1532325}, {'name': 'Deborah Taylor', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c693b39251411d30016f78', 'id': 1536539}, {'name': 'Ryan Church', 'gender': 0, 'department': 'Crew', 'job': 'Visual Effects Art Director', 'credit_id': '58c68e84c3a36840f60153a1', 'id': 1546844}, {'name': 'Camille Henderson', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Key Makeup Artist', 'credit_id': '58c693659251411d550173be', 'id': 1549655}, {'name': 'Tom Struthers', 'gender': 0, 'department': 'Crew', 'job': 'Stunt Coordinator', 'credit_id': '58c68fd29251411d30016d3f', 'id': 1550851}, {'name': 'Liam Georgensen', 'gender': 0, 'department': 'Art', 'job': 'Art Department Assistant', 'credit_id': '58c692bfc3a36840b8016df9', 'id': 1551810}, {'name': 'Lavinia Waters', 'gender': 0, 'department': 'Art', 'job': 'Art Department Coordinator', 'credit_id': '58c692869251411d30016ed9', 'id': 1561994}, {'name': 'Greg T. Moon', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c697f89251411d30017205', 'id': 1613336}, {'name': 'Richard Daldry', 'gender': 0, 'department': 'Production', 'job': 'Production Coordinator', 'credit_id': '58c69a07c3a36841200159ae', 'id': 1640350}, {'name': 'Stephen Finn', 'gender': 2, 'department': 'Sound', 'job': 'Boom Operator', 'credit_id': '58c69979c3a368413b015eef', 'id': 1658269}, {'name': 'Tom Castronovo', 'gender': 0, 'department': 'Art', 'job': 'Art Department Assistant', 'credit_id': '58c692e4c3a36840f601564a', 'id': 1661321}, {'name': 'Katherine McCormack', 'gender': 0, 'department': 'Crew', 'job': 'Unit Publicist', 'credit_id': '58c69dadc3a36841280157a4', 'id': 1686002}, {'name': 'Steve Harding', 'gender': 0, 'department': 'Production', 'job': 'Unit Production Manager', 'credit_id': '58c689439251411d15016ed6', 'id': 1697623}, {'name': 'Erik Jessen', 'gender': 0, 'department': 'Editing', 'job': 'Additional Editing', 'credit_id': '58c68ebdc3a3684128014e11', 'id': 1710258}, {'name': 'Tommy Gormley', 'gender': 0, 'department': 'Directing', 'job': 'First Assistant Director', 'credit_id': '58c689739251411d47017af1', 'id': 1750922}, {'name': 'Sarah Ginn', 'gender': 0, 'department': 'Art', 'job': 'Art Department Assistant', 'credit_id': '58c692c7c3a36841300150c2', 'id': 1761112}, {'name': 'Ben Dixon', 'gender': 0, 'department': 'Directing', 'job': 'Second Assistant Director', 'credit_id': '58c689aa9251411d55016d59', 'id': 1775681}, {'name': 'Andrew M. Ward', 'gender': 2, 'department': 'Directing', 'job': 'Second Assistant Director', 'credit_id': '58c68a859251411d1901746d', 'id': 1775682}, {'name': 'Stacey Newton', 'gender': 0, 'department': 'Art', 'job': 'Art Department Coordinator', 'credit_id': '58c692a4c3a368413b015a64', 'id': 1775687}, {'name': 'Rachel Corbould', 'gender': 0, 'department': 'Art', 'job': 'Art Department Assistant', 'credit_id': '58c692b6c3a368412001546d', 'id': 1775688}, {'name': 'Jake Hall', 'gender': 0, 'department': 'Art', 'job': 'Art Department Assistant', 'credit_id': '58c692d4c3a368413b015a88', 'id': 1775689}, {'name': 'Gemma Richards', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Key Makeup Artist', 'credit_id': '58c693589251411d0d017fb3', 'id': 1775690}, {'name': 'Sara Riesel', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c693fe9251411d55017423', 'id': 1775691}, {'name': 'Paul Boyce', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c69407c3a368413b015b42', 'id': 1775692}, {'name': 'Mandy Gold', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '58c694189251411d19017ab6', 'id': 1775693}, {'name': 'Candice Banks', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Hairstylist', 'credit_id': '58c698989251411d0d01836e', 'id': 1775701}, {'name': 'Gary Machin', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Hairstylist', 'credit_id': '58c698a59251411d19017de5', 'id': 1775702}, {'name': 'Noel Espinosa', 'gender': 0, 'department': 'Sound', 'job': 'Boom Operator', 'credit_id': '58c69994c3a36840b80172dd', 'id': 1775704}, {'name': 'Meredith Humbracht', 'gender': 0, 'department': 'Production', 'job': 'Production Coordinator', 'credit_id': '58c69a309251411d110178c9', 'id': 1775707}, {'name': 'Gary Hymns', 'gender': 0, 'department': 'Camera', 'job': 'Key Grip', 'credit_id': '58c69d39c3a368410c0163fd', 'id': 1775718}, {'name': 'Thomas Gibson', 'gender': 0, 'department': 'Camera', 'job': 'Key Grip', 'credit_id': '58c69da6c3a368413b01620f', 'id': 1775721}, {'name': 'Danton Burroughs', 'gender': 0, 'department': 'Crew', 'job': 'Thanks', 'credit_id': '58c69ec49251411d55017be6', 'id': 1775723}, {'name': 'Karin Silvestri', 'gender': 1, 'department': 'Crew', 'job': 'Stunts', 'credit_id': '591264bac3a368646b04fda5', 'id': 1813644}]

Common Values

Value	Count	Frequency (%)
[]	28	0.6%
[{'name': 'Stephen E. 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Bentley', 'gender': 0, 'department': 'Art', 'job': 'Property Master', 'credit_id': '5953ca269251412ac703b416', 'id': 1840702}, {'name': 'Ahart Powers III', 'gender': 0, 'department': 'Art', 'job': 'Art Department Coordinator', 'credit_id': '5953ca9f9251412ac703b468', 'id': 1840712}, {'name': 'Paul Maraio', 'gender': 0, 'department': 'Sound', 'job': 'Sound Designer', 'credit_id': '5953cb59c3a36834e5021db5', 'id': 1840713}, {'name': 'Brian McPherson', 'gender': 0, 'department': 'Sound', 'job': 'Sound Editor', 'credit_id': '5953cbb092514168bf00bb51', 'id': 1840714}, {'name': 'Rex M. Teese', 'gender': 0, 'department': 'Visual Effects', 'job': 'Visual Effects Coordinator', 'credit_id': '5953cc61c3a368151c034e2f', 'id': 1840715}, {'name': 'Jamie A. Marlowe', 'gender': 0, 'department': 'Camera', 'job': 'Camera Operator', 'credit_id': '5953cd0d92514168bf00bc62', 'id': 1840716}, {'name': 'Gerry Sackman', 'gender': 0, 'department': 'Sound', 'job': 'Music Editor', 'credit_id': '5953cdbac3a368138803c960', 'id': 1840720}]	1	< 0.1%
[{'name': 'Margery Simkin', 'gender': 1, 'department': 'Production', 'job': 'Casting', 'credit_id': '596be3f99251413b20005681', 'id': 6347}, {'name': 'Mary Zophres', 'gender': 1, 'department': 'Costume & Make-Up', 'job': 'Costume Design', 'credit_id': '596be426c3a3684c1000506a', 'id': 7418}, {'name': 'Hart Bochner', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe45f29251416c75067e17', 'id': 7678}, {'name': 'David Coatsworth', 'gender': 2, 'department': 'Production', 'job': 'Unit Production Manager', 'credit_id': '596ce7a79251410a31001309', 'id': 12374}, {'name': 'Reynaldo Villalobos', 'gender': 2, 'department': 'Camera', 'job': 'Director of Photography', 'credit_id': '596be5239251413b57005874', 'id': 17948}, {'name': 'Paul Schiff', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '596be57f9251413b1c005bac', 'id': 18344}, {'name': 'Zak Penn', 'gender': 2, 'department': 'Writing', 'job': 'Writer', 'credit_id': '52fe45f29251416c75067e23', 'id': 11011}, {'name': 'Nicholas C. Smith', 'gender': 2, 'department': 'Editing', 'job': 'Editor', 'credit_id': '596be4ca9251413b24005cae', 'id': 28161}, {'name': 'Steven J. Jordan', 'gender': 0, 'department': 'Art', 'job': 'Production Design', 'credit_id': '596be5079251413b3d005b1f', 'id': 38411}, {'name': 'Adam Leff', 'gender': 0, 'department': 'Writing', 'job': 'Writer', 'credit_id': '52fe45f29251416c75067e1d', 'id': 57872}, {'name': 'Ralph Sall', 'gender': 2, 'department': 'Crew', 'job': 'Executive Music Producer', 'credit_id': '596be4729251413b6000575e', 'id': 73137}, {'name': 'Martin Walters', 'gender': 2, 'department': 'Directing', 'job': 'First Assistant Director', 'credit_id': '596ce803c3a3682a390017c0', 'id': 977988}, {'name': 'Walter Gasparovic', 'gender': 0, 'department': 'Directing', 'job': 'Second Assistant Director', 'credit_id': '596ce81fc3a36829da001534', 'id': 1016148}, {'name': 'Barry Sabath', 'gender': 0, 'department': 'Production', 'job': 'Co-Producer', 'credit_id': '596be55a9251413b6e0059a7', 'id': 1852804}]	1	< 0.1%
Other values (4766)	4766	99.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
department	131726	7.2%
job	129587	7.0%
id	129581	7.0%
name	129581	7.0%
gender	129581	7.0%
credit_id	129581	7.0%
0	74817	4.1%
2	43000	2.3%
production	34158	1.9%
sound	23332	1.3%
Other values (217295)	885403	48.1%

Most occurring characters

Value	Count	Frequency (%)
'	2590811	13.6%
	1835557	9.7%
e	1285097	6.8%
d	883283	4.6%
r	790804	4.2%
:	777486	4.1%
,	772739	4.1%
i	735774	3.9%
a	690132	3.6%
t	688735	3.6%
Other values (70)	7948467	41.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	8664616	45.6%
Other Punctuation	4173996	22.0%
Decimal Number	3228879	17.0%
Space Separator	1835557	9.7%
Uppercase Letter	681142	3.6%
Close Punctuation	134390	0.7%
Open Punctuation	134390	0.7%
Connector Punctuation	129581	0.7%
Dash Punctuation	16333	0.1%
Math Symbol	1	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	1285097	14.8%
d	883283	10.2%
r	790804	9.1%
i	735774	8.5%
a	690132	8.0%
t	688735	7.9%
n	667167	7.7%
c	463442	5.3%
o	462325	5.3%
m	331518	3.8%
Other values (16)	1666339	19.2%

Uppercase Letter

Value	Count	Frequency (%)
C	82238	12.1%
S	78811	11.6%
P	75580	11.1%
D	58851	8.6%
M	52913	7.8%
E	51275	7.5%
A	51057	7.5%
W	22998	3.4%
J	22696	3.3%
B	21992	3.2%
Other values (16)	162731	23.9%

Decimal Number

Value	Count	Frequency (%)
0	466612	14.5%
1	395475	12.2%
5	388828	12.0%
3	344745	10.7%
4	334144	10.3%
2	326032	10.1%
6	275883	8.5%
8	260121	8.1%
9	220576	6.8%
7	216463	6.7%

Other Punctuation

Value	Count	Frequency (%)
'	2590811	62.1%
:	777486	18.6%
,	772739	18.5%
.	12347	0.3%
&	11707	0.3%
\	6736	0.2%
"	2110	0.1%
/	60	< 0.1%

Close Punctuation

Value	Count	Frequency (%)
}	129581	96.4%
]	4803	3.6%
)	6	< 0.1%

Open Punctuation

Value	Count	Frequency (%)
{	129581	96.4%
[	4803	3.6%
(	6	< 0.1%

Space Separator

Value	Count	Frequency (%)
	1835557	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	129581	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	16333	100.0%

Math Symbol

Value	Count	Frequency (%)
\|	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	9653127	50.8%
Latin	9345758	49.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	1285097	13.8%
d	883283	9.5%
r	790804	8.5%
i	735774	7.9%
a	690132	7.4%
t	688735	7.4%
n	667167	7.1%
c	463442	5.0%
o	462325	4.9%
m	331518	3.5%
Other values (42)	2347481	25.1%

Common

Value	Count	Frequency (%)
'	2590811	26.8%
	1835557	19.0%
:	777486	8.1%
,	772739	8.0%
0	466612	4.8%
1	395475	4.1%
5	388828	4.0%
3	344745	3.6%
4	334144	3.5%
2	326032	3.4%
Other values (18)	1420698	14.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	18998885	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
'	2590811	13.6%
	1835557	9.7%
e	1285097	6.8%
d	883283	4.6%
r	790804	4.2%
:	777486	4.1%
,	772739	4.1%
i	735774	3.9%
a	690132	3.6%
t	688735	3.6%
Other values (70)	7948467	41.8%

director
Categorical

Distinct	2349
Distinct (%)	49.2%
Missing	30
Missing (%)	0.6%
Memory size	37.6 KiB

Steven Spielberg	27
Woody Allen	21
Clint Eastwood	20
Martin Scorsese	20
Ridley Scott	16
Other values (2344)	4669

Length

Max length	42
Median length	28
Mean length	13.281374
Min length	3

Characters and Unicode

Total characters	63392
Distinct characters	68
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1475 ?
Unique (%)	30.9%

Sample

1st row	James Cameron
2nd row	Gore Verbinski
3rd row	Sam Mendes
4th row	Christopher Nolan
5th row	Andrew Stanton

Common Values

Value	Count	Frequency (%)
Steven Spielberg	27	0.6%
Woody Allen	21	0.4%
Clint Eastwood	20	0.4%
Martin Scorsese	20	0.4%
Ridley Scott	16	0.3%
Robert Rodriguez	16	0.3%
Spike Lee	16	0.3%
Renny Harlin	15	0.3%
Steven Soderbergh	15	0.3%
Oliver Stone	14	0.3%
Other values (2339)	4593	95.6%
(Missing)	30	0.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
john	173	1.7%
david	145	1.5%
michael	124	1.2%
robert	89	0.9%
james	87	0.9%
peter	79	0.8%
richard	78	0.8%
paul	72	0.7%
scott	62	0.6%
steven	57	0.6%
Other values (2905)	8971	90.3%

Most occurring characters

Value	Count	Frequency (%)
e	5990	9.4%
	5169	8.2%
a	5099	8.0%
n	4523	7.1%
r	4288	6.8%
o	3686	5.8%
i	3591	5.7%
l	2887	4.6%
t	2235	3.5%
s	2019	3.2%
Other values (58)	23905	37.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	47140	74.4%
Uppercase Letter	10130	16.0%
Space Separator	5169	8.2%
Decimal Number	461	0.7%
Other Punctuation	409	0.6%
Dash Punctuation	83	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	5990	12.7%
a	5099	10.8%
n	4523	9.6%
r	4288	9.1%
o	3686	7.8%
i	3591	7.6%
l	2887	6.1%
t	2235	4.7%
s	2019	4.3%
h	1789	3.8%
Other values (16)	11033	23.4%

Uppercase Letter

Value	Count	Frequency (%)
S	990	9.8%
J	895	8.8%
M	858	8.5%
R	741	7.3%
C	692	6.8%
B	642	6.3%
D	587	5.8%
A	530	5.2%
L	488	4.8%
G	468	4.6%
Other values (16)	3239	32.0%

Decimal Number

Value	Count	Frequency (%)
0	300	65.1%
1	50	10.8%
9	43	9.3%
6	20	4.3%
3	18	3.9%
4	10	2.2%
5	9	2.0%
7	6	1.3%
8	3	0.7%
2	2	0.4%

Other Punctuation

Value	Count	Frequency (%)
.	228	55.7%
\	155	37.9%
'	21	5.1%
,	5	1.2%

Space Separator

Value	Count	Frequency (%)
	5169	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	83	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	57270	90.3%
Common	6122	9.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	5990	10.5%
a	5099	8.9%
n	4523	7.9%
r	4288	7.5%
o	3686	6.4%
i	3591	6.3%
l	2887	5.0%
t	2235	3.9%
s	2019	3.5%
h	1789	3.1%
Other values (42)	21163	37.0%

Common

Value	Count	Frequency (%)
	5169	84.4%
0	300	4.9%
.	228	3.7%
\	155	2.5%
-	83	1.4%
1	50	0.8%
9	43	0.7%
'	21	0.3%
6	20	0.3%
3	18	0.3%
Other values (6)	35	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	63392	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	5990	9.4%
	5169	8.2%
a	5099	8.0%
n	4523	7.1%
r	4288	6.8%
o	3686	5.8%
i	3591	5.7%
l	2887	4.6%
t	2235	3.5%
s	2019	3.2%
Other values (58)	23905	37.7%

Auto

Heatmap
Table

	df_index	budget	id	popularity	revenue	runtime	vote_average	vote_count	original_language	status
df_index	1.000	-0.852	0.244	-0.610	-0.672	-0.357	-0.022	-0.619	0.067	0.065
budget	-0.852	1.000	-0.246	0.649	0.757	0.326	0.066	0.663	0.000	0.000
id	0.244	-0.246	1.000	-0.278	-0.292	-0.216	-0.266	-0.297	0.089	0.048
popularity	-0.610	0.649	-0.278	1.000	0.777	0.302	0.359	0.960	0.000	0.000
revenue	-0.672	0.757	-0.292	0.777	1.000	0.317	0.243	0.804	0.000	0.000
runtime	-0.357	0.326	-0.216	0.302	0.317	1.000	0.398	0.304	0.020	0.029
vote_average	-0.022	0.066	-0.266	0.359	0.243	0.398	1.000	0.381	0.059	0.131
vote_count	-0.619	0.663	-0.297	0.960	0.804	0.304	0.381	1.000	0.000	0.000
original_language	0.067	0.000	0.089	0.000	0.000	0.020	0.059	0.000	1.000	0.275
status	0.065	0.000	0.048	0.000	0.000	0.029	0.131	0.000	0.275	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

First rows
Last rows

	df_index	budget	genres	homepage	id	keywords	original_language	original_title	overview	popularity	production_companies	production_countries	release_date	revenue	runtime	spoken_languages	status	tagline	title	vote_average	vote_count	cast	crew	director
0	0	237000000	Action Adventure Fantasy Science Fiction	http://www.avatarmovie.com/	19995	culture clash future space war space colony society	en	Avatar	In the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization.	150.437577	[{"name": "Ingenious Film Partners", "id": 289}, {"name": "Twentieth Century Fox Film Corporation", "id": 306}, {"name": "Dune Entertainment", "id": 444}, {"name": "Lightstorm Entertainment", "id": 574}]	[{"iso_3166_1": "US", "name": "United States of America"}, {"iso_3166_1": "GB", "name": "United Kingdom"}]	2009-12-10	2787965087	162.0	[{"iso_639_1": "en", "name": "English"}, {"iso_639_1": "es", "name": "Espa\u00f1ol"}]	Released	Enter the World of Pandora.	Avatar	7.2	11800	Sam Worthington Zoe Saldana Sigourney Weaver Stephen Lang Michelle Rodriguez	[{'name': 'Stephen E. Rivkin', 'gender': 0, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe48009251416c750aca23', 'id': 1721}, {'name': 'Rick Carter', 'gender': 2, 'department': 'Art', 'job': 'Production Design', 'credit_id': '539c47ecc3a36810e3001f87', 'id': 496}, {'name': 'Christopher Boyes', 'gender': 0, 'department': 'Sound', 'job': 'Sound Designer', 'credit_id': '54491c89c3a3680fb4001cf7', 'id': 900}, {'name': 'Christopher Boyes', 'gender': 0, 'department': 'Sound', 'job': 'Supervising Sound Editor', 'credit_id': '54491cb70e0a267480001bd0', 'id': 900}, {'name': 'Mali Finn', 'gender': 1, 'department': 'Production', 'job': 'Casting', 'credit_id': '539c4a4cc3a36810c9002101', 'id': 1262}, {'name': 'James Horner', 'gender': 2, 'department': 'Sound', 'job': 'Original Music Composer', 'credit_id': '5544ee3b925141499f0008fc', 'id': 1729}, {'name': 'James Cameron', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe48009251416c750ac9c3', 'id': 2710}, {'name': 'James Cameron', 'gender': 2, 'department': 'Writing', 'job': 'Writer', 'credit_id': '52fe48009251416c750ac9d9', 'id': 2710}, {'name': 'James Cameron', 'gender': 2, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe48009251416c750aca17', 'id': 2710}, {'name': 'James Cameron', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe48009251416c750aca29', 'id': 2710}, {'name': 'James Cameron', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '52fe48009251416c750aca3f', 'id': 2710}, {'name': 'Andrew Menzies', 'gender': 2, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '539c4987c3a36810ba0021a4', 'id': 7236}, {'name': 'Jill Brooks', 'gender': 0, 'department': 'Visual Effects', 'job': 'Visual Effects Producer', 'credit_id': '549598c3c3a3686ae9004383', 'id': 6690}, {'name': 'Margery Simkin', 'gender': 1, 'department': 'Production', 'job': 'Casting', 'credit_id': '52fe48009251416c750aca4b', 'id': 6347}, {'name': 'Kevin Ishioka', 'gender': 2, 'department': 'Art', 'job': 'Supervising Art Director', 'credit_id': '570b6f419251417da70032fe', 'id': 6878}, {'name': 'Dick Bernstein', 'gender': 0, 'department': 'Sound', 'job': 'Music Editor', 'credit_id': '5495a0fac3a3686ae9004468', 'id': 6883}, {'name': 'Shannon Mills', 'gender': 0, 'department': 'Sound', 'job': 'Sound Effects Editor', 'credit_id': '54959706c3a3686af3003e81', 'id': 8159}, {'name': 'Dennie Thorpe', 'gender': 0, 'department': 'Sound', 'job': 'Foley', 'credit_id': '54491d58c3a3680fb1001ccb', 'id': 8160}, {'name': 'Jana Vance', 'gender': 0, 'department': 'Sound', 'job': 'Foley', 'credit_id': '54491d6cc3a3680fa5001b2c', 'id': 8163}, {'name': 'Deborah Lynn Scott', 'gender': 1, 'department': 'Costume & Make-Up', 'job': 'Costume Design', 'credit_id': '52fe48009251416c750aca57', 'id': 8527}, {'name': 'Jon Landau', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe48009251416c750aca2f', 'id': 8529}, {'name': 'Sean Haworth', 'gender': 0, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '539c4937c3a36810ba002194', 'id': 9618}, {'name': 'Kim Sinclair', 'gender': 1, 'department': 'Art', 'job': 'Set Decoration', 'credit_id': '539c49b6c3a36810c10020e6', 'id': 12653}, {'name': 'Kim Sinclair', 'gender': 1, 'department': 'Art', 'job': 'Supervising Art Director', 'credit_id': '570b6f2f9251413a0e00020d', 'id': 12653}, {'name': 'Richard F. Mays', 'gender': 2, 'department': 'Art', 'job': 'Set Designer', 'credit_id': '54491a6c0e0a26748c001b19', 'id': 14350}, {'name': 'Laeta Kalogridis', 'gender': 1, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '56928cf4c3a3684cff0025c4', 'id': 20294}, {'name': 'Mayes C. Rubeo', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Costume Design', 'credit_id': '52fe48009251416c750aca51', 'id': 17675}, {'name': 'Mauro Fiore', 'gender': 2, 'department': 'Camera', 'job': 'Director of Photography', 'credit_id': '52fe48009251416c750aca11', 'id': 18265}, {'name': 'Scott Herbertson', 'gender': 0, 'department': 'Art', 'job': 'Set Designer', 'credit_id': '5449194d0e0a26748f001b39', 'id': 42281}, {'name': 'Woody Schultz', 'gender': 0, 'department': 'Crew', 'job': 'Stunts', 'credit_id': '52fe48009251416c750aca05', 'id': 42288}, {'name': 'Linda DeVetta', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Makeup Artist', 'credit_id': '5592aefb92514152de0010f5', 'id': 29067}, {'name': 'Linda DeVetta', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Hairstylist', 'credit_id': '5592afa492514152de00112c', 'id': 29067}, {'name': 'Richard Bluck', 'gender': 2, 'department': 'Camera', 'job': 'Camera Operator', 'credit_id': '54959ed592514130fc002e5d', 'id': 33302}, {'name': 'Simon Bright', 'gender': 2, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '539c4891c3a36810ba002147', 'id': 33303}, {'name': 'Richard Martin', 'gender': 0, 'department': 'Visual Effects', 'job': 'Visual Effects Supervisor', 'credit_id': '54959c069251417a81001f3a', 'id': 113145}, {'name': 'Steve R. Moore', 'gender': 2, 'department': 'Crew', 'job': 'Visual Effects Editor', 'credit_id': '54959a0dc3a3680ff5002c8d', 'id': 58188}, {'name': 'John Refoua', 'gender': 2, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe48009251416c750aca1d', 'id': 58871}, {'name': 'Karl J. 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1	1	300000000	Adventure Fantasy Action	http://disney.go.com/disneypictures/pirates/	285	ocean drug abuse exotic island east india trading company love of one's life	en	Pirates of the Caribbean: At World's End	Captain Barbossa, long believed to be dead, has come back to life and is headed to the edge of the Earth with Will Turner and Elizabeth Swann. But nothing is quite as it seems.	139.082615	[{"name": "Walt Disney Pictures", "id": 2}, {"name": "Jerry Bruckheimer Films", "id": 130}, {"name": "Second Mate Productions", "id": 19936}]	[{"iso_3166_1": "US", "name": "United States of America"}]	2007-05-19	961000000	169.0	[{"iso_639_1": "en", "name": "English"}]	Released	At the end of the world, the adventure begins.	Pirates of the Caribbean: At World's End	6.9	4500	Johnny Depp Orlando Bloom Keira Knightley Stellan Skarsg\u00e5rd Chow Yun-fat	[{'name': 'Dariusz Wolski', 'gender': 2, 'department': 'Camera', 'job': 'Director of Photography', 'credit_id': '52fe4232c3a36847f800b579', 'id': 120}, {'name': 'Gore Verbinski', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe4232c3a36847f800b4fd', 'id': 1704}, {'name': 'Jerry Bruckheimer', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4232c3a36847f800b54f', 'id': 770}, {'name': 'Ted Elliott', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '52fe4232c3a36847f800b503', 'id': 1705}, {'name': 'Terry Rossio', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '52fe4232c3a36847f800b509', 'id': 1706}, {'name': 'Stephen E. 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2	2	245000000	Action Adventure Crime	http://www.sonypictures.com/movies/spectre/	206647	spy based on novel secret agent sequel mi6	en	Spectre	A cryptic message from Bond’s past sends him on a trail to uncover a sinister organization. While M battles political forces to keep the secret service alive, Bond peels back the layers of deceit to reveal the terrible truth behind SPECTRE.	107.376788	[{"name": "Columbia Pictures", "id": 5}, {"name": "Danjaq", "id": 10761}, {"name": "B24", "id": 69434}]	[{"iso_3166_1": "GB", "name": "United Kingdom"}, {"iso_3166_1": "US", "name": "United States of America"}]	2015-10-26	880674609	148.0	[{"iso_639_1": "fr", "name": "Fran\u00e7ais"}, {"iso_639_1": "en", "name": "English"}, {"iso_639_1": "es", "name": "Espa\u00f1ol"}, {"iso_639_1": "it", "name": "Italiano"}, {"iso_639_1": "de", "name": "Deutsch"}]	Released	A Plan No One Escapes	Spectre	6.3	4466	Daniel Craig Christoph Waltz L\u00e9a Seydoux Ralph Fiennes Monica Bellucci	[{'name': 'Thomas Newman', 'gender': 2, 'department': 'Sound', 'job': 'Original Music Composer', 'credit_id': '54805967c3a36829b5002c41', 'id': 153}, {'name': 'Sam Mendes', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': 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3	3	250000000	Action Crime Drama Thriller	http://www.thedarkknightrises.com/	49026	dc comics crime fighter terrorist secret identity burglar	en	The Dark Knight Rises	Following the death of District Attorney Harvey Dent, Batman assumes responsibility for Dent's crimes to protect the late attorney's reputation and is subsequently hunted by the Gotham City Police Department. Eight years later, Batman encounters the mysterious Selina Kyle and the villainous Bane, a new terrorist leader who overwhelms Gotham's finest. The Dark Knight resurfaces to protect a city that has branded him an enemy.	112.312950	[{"name": "Legendary Pictures", "id": 923}, {"name": "Warner Bros.", "id": 6194}, {"name": "DC Entertainment", "id": 9993}, {"name": "Syncopy", "id": 9996}]	[{"iso_3166_1": "US", "name": "United States of America"}]	2012-07-16	1084939099	165.0	[{"iso_639_1": "en", "name": "English"}]	Released	The Legend Ends	The Dark Knight Rises	7.6	9106	Christian Bale Michael Caine Gary Oldman Anne Hathaway Tom Hardy	[{'name': 'Hans Zimmer', 'gender': 2, 'department': 'Sound', 'job': 'Original Music Composer', 'credit_id': '52fe4781c3a36847f81398c3', 'id': 947}, {'name': 'Charles Roven', 'gender': 0, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4781c3a36847f8139899', 'id': 282}, {'name': 'Christopher Nolan', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '52fe4781c3a36847f813991b', 'id': 525}, {'name': 'Christopher Nolan', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe4781c3a36847f8139865', 'id': 525}, {'name': 'Christopher Nolan', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4781c3a36847f8139893', 'id': 525}, {'name': 'Christopher Nolan', 'gender': 2, 'department': 'Writing', 'job': 'Story', 'credit_id': '52fe4781c3a36847f8139915', 'id': 525}, {'name': 'Jonathan Nolan', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '52fe4781c3a36847f813990f', 'id': 527}, {'name': 'Emma Thomas', 'gender': 1, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4781c3a36847f813989f', 'id': 556}, {'name': 'Wally Pfister', 'gender': 2, 'department': 'Camera', 'job': 'Director of Photography', 'credit_id': '52fe4781c3a36847f81398c9', 'id': 559}, {'name': 'Wally Pfister', 'gender': 2, 'department': 'Camera', 'job': 'Camera Operator', 'credit_id': '54c37788c3a3681421011a07', 'id': 559}, {'name': 'John Papsidera', 'gender': 0, 'department': 'Production', 'job': 'Casting', 'credit_id': '52fe4781c3a36847f81398d5', 'id': 561}, {'name': 'David S. 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4	4	260000000	Action Adventure Science Fiction	http://movies.disney.com/john-carter	49529	based on novel mars medallion space travel princess	en	John Carter	John Carter is a war-weary, former military captain who's inexplicably transported to the mysterious and exotic planet of Barsoom (Mars) and reluctantly becomes embroiled in an epic conflict. It's a world on the brink of collapse, and Carter rediscovers his humanity when he realizes the survival of Barsoom and its people rests in his hands.	43.926995	[{"name": "Walt Disney Pictures", "id": 2}]	[{"iso_3166_1": "US", "name": "United States of America"}]	2012-03-07	284139100	132.0	[{"iso_639_1": "en", "name": "English"}]	Released	Lost in our world, found in another.	John Carter	6.1	2124	Taylor Kitsch Lynn Collins Samantha Morton Willem Dafoe Thomas Haden Church	[{'name': 'Andrew Stanton', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '52fe479ac3a36847f813eaa3', 'id': 7}, {'name': 'Andrew Stanton', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe479ac3a36847f813ea65', 'id': 7}, {'name': 'John Lasseter', 'gender': 2, 'department': 'Crew', 'job': 'Thanks', 'credit_id': '58c69e819251411d30017673', 'id': 7879}, {'name': 'Colin Wilson', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe479ac3a36847f813eac5', 'id': 490}, {'name': 'Gail Stevens', 'gender': 2, 'department': 'Production', 'job': 'Casting', 'credit_id': '58c68f2b9251411d30016cf2', 'id': 2073}, {'name': 'Tom Johnson', 'gender': 2, 'department': 'Sound', 'job': 'Sound Re-Recording Mixer', 'credit_id': '58c68ef19251411d62016ec3', 'id': 3996}, {'name': 'Eric Zumbrunnen', 'gender': 2, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe479ac3a36847f813ead7', 'id': 6958}, {'name': 'Michael Silvers', 'gender': 0, 'department': 'Editing', 'job': 'Dialogue Editor', 'credit_id': '58c69a9ec3a36840b801738e', 'id': 8158}, {'name': 'Juan Peralta', 'gender': 0, 'department': 'Sound', 'job': 'Sound Re-Recording Mixer', 'credit_id': '58c68f1ec3a368413b015877', 'id': 8166}, {'name': 'Paul Gooch', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Key Makeup Artist', 'credit_id': '58c69340c3a36841200154c9', 'id': 8412}, {'name': 'Paki Smith', 'gender': 0, 'department': 'Art', 'job': 'Set Decoration', 'credit_id': '58c69cc0c3a368413001574a', 'id': 12039}, {'name': 'Ed Catmull', 'gender': 0, 'department': 'Crew', 'job': 'Thanks', 'credit_id': '58c69e9e9251411d11017c02', 'id': 12895}, {'name': 'Steve Jobs', 'gender': 2, 'department': 'Crew', 'job': 'In Memory Of', 'credit_id': '58c689079251411d19017350', 'id': 12897}, {'name': 'Bill Corso', 'gender': 2, 'department': 'Costume & Make-Up', 'job': 'Makeup Designer', 'credit_id': '56abe29d9251417e22003953', 'id': 15017}, {'name': 'Robert Woodruff', 'gender': 2, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '58c691fc9251411d30016e75', 'id': 14762}, {'name': 'Nathan Crowley', 'gender': 2, 'department': 'Art', 'job': 'Production Design', 'credit_id': '52fe479ac3a36847f813eae3', 'id': 15327}, {'name': 'Michael Giacchino', 'gender': 2, 'department': 'Sound', 'job': 'Music', 'credit_id': '58c6888bc3a36840f6014f95', 'id': 15347}, {'name': 'Daniel Mindel', 'gender': 0, 'department': 'Camera', 'job': 'Director of Photography', 'credit_id': '52fe479ac3a36847f813ead1', 'id': 15348}, {'name': 'Stephen M. 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5	5	258000000	Fantasy Action Adventure	http://www.sonypictures.com/movies/spider-man3/	559	dual identity amnesia sandstorm love of one's life forgiveness	en	Spider-Man 3	The seemingly invincible Spider-Man goes up against an all-new crop of villain – including the shape-shifting Sandman. While Spider-Man’s superpowers are altered by an alien organism, his alter ego, Peter Parker, deals with nemesis Eddie Brock and also gets caught up in a love triangle.	115.699814	[{"name": "Columbia Pictures", "id": 5}, {"name": "Laura Ziskin Productions", "id": 326}, {"name": "Marvel Enterprises", "id": 19551}]	[{"iso_3166_1": "US", "name": "United States of America"}]	2007-05-01	890871626	139.0	[{"iso_639_1": "en", "name": "English"}, {"iso_639_1": "fr", "name": "Fran\u00e7ais"}]	Released	The battle within.	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6	6	260000000	Animation Family	http://disney.go.com/disneypictures/tangled/	38757	hostage magic horse fairy tale musical	en	Tangled	When the kingdom's most wanted-and most charming-bandit Flynn Rider hides out in a mysterious tower, he's taken hostage by Rapunzel, a beautiful and feisty tower-bound teen with 70 feet of magical, golden hair. Flynn's curious captor, who's looking for her ticket out of the tower where she's been locked away for years, strikes a deal with the handsome thief and the unlikely duo sets off on an action-packed escapade, complete with a super-cop horse, an over-protective chameleon and a gruff gang of pub thugs.	48.681969	[{"name": "Walt Disney Pictures", "id": 2}, {"name": "Walt Disney Animation Studios", "id": 6125}]	[{"iso_3166_1": "US", "name": "United States of America"}]	2010-11-24	591794936	100.0	[{"iso_639_1": "en", "name": "English"}]	Released	They're taking adventure to new lengths.	Tangled	7.4	3330	Zachary Levi Mandy Moore Donna Murphy Ron Perlman M.C. 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7	7	280000000	Action Adventure Science Fiction	http://marvel.com/movies/movie/193/avengers_age_of_ultron	99861	marvel comic sequel superhero based on comic book vision	en	Avengers: Age of Ultron	When Tony Stark tries to jumpstart a dormant peacekeeping program, things go awry and Earth’s Mightiest Heroes are put to the ultimate test as the fate of the planet hangs in the balance. As the villainous Ultron emerges, it is up to The Avengers to stop him from enacting his terrible plans, and soon uneasy alliances and unexpected action pave the way for an epic and unique global adventure.	134.279229	[{"name": "Marvel Studios", "id": 420}, {"name": "Prime Focus", "id": 15357}, {"name": "Revolution Sun Studios", "id": 76043}]	[{"iso_3166_1": "US", "name": "United States of America"}]	2015-04-22	1405403694	141.0	[{"iso_639_1": "en", "name": "English"}]	Released	A New Age Has Come.	Avengers: Age of Ultron	7.3	6767	Robert Downey Jr. Chris Hemsworth Mark Ruffalo Chris Evans Scarlett Johansson	[{'name': 'Danny Elfman', 'gender': 2, 'department': 'Sound', 'job': 'Original Music Composer', 'credit_id': '55d5f7d4c3a3683e7e0016eb', 'id': 531}, {'name': 'Christopher Boyes', 'gender': 0, 'department': 'Sound', 'job': 'Supervising Sound Editor', 'credit_id': '55f7d48892514103b60074ad', 'id': 900}, {'name': 'Christopher Boyes', 'gender': 0, 'department': 'Sound', 'job': 'Sound Re-Recording Mixer', 'credit_id': '55f7d30d9251416d96004fd1', 'id': 900}, {'name': 'Sarah Finn', 'gender': 1, 'department': 'Production', 'job': 'Casting', 'credit_id': '550b070ec3a3684874001c9a', 'id': 7232}, {'name': 'Brian Tyler', 'gender': 2, 'department': 'Sound', 'job': 'Original Music Composer', 'credit_id': '55d5f7e2c3a3687b990044bd', 'id': 6041}, {'name': 'Stan Lee', 'gender': 2, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '52fe4a449251416c750e3451', 'id': 7624}, 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Green', 'gender': 0, 'department': 'Visual Effects', 'job': 'Visual Effects', 'credit_id': '553745c2c3a3681785004fe2', 'id': 1457635}, {'name': 'Katy Wood', 'gender': 0, 'department': 'Sound', 'job': 'ADR & Dubbing', 'credit_id': '55f7d22fc3a3686d1800b842', 'id': 1458578}, {'name': 'Luca Marco Paracels', 'gender': 2, 'department': 'Production', 'job': 'Co-Producer', 'credit_id': '5751e5b0c3a36853b3000533', 'id': 1477203}, {'name': 'Richard Roles', 'gender': 2, 'department': 'Camera', 'job': 'Helicopter Camera', 'credit_id': '55f7d94e92514103b600753b', 'id': 1494209}, {'name': 'Domenico Sica', 'gender': 0, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '55f7cf74925141504d001186', 'id': 1510429}, {'name': "Chris 'Flimsy' Howes", 'gender': 0, 'department': 'Art', 'job': 'Set Decoration', 'credit_id': '55f7d001c3a3680a0d00d3db', 'id': 1510430}, {'name': 'Stefano De Nardis', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Costume Supervisor', 'credit_id': '55f7d0bdc3a3686d1800b81a', 'id': 1510431}, {'name': 'Ben Vokes', 'gender': 0, 'department': 'Crew', 'job': 'Special Effects Coordinator', 'credit_id': '55f7d4ffc3a3686d0300ccb4', 'id': 1510438}, {'name': 'Ki S. 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8	8	250000000	Adventure Fantasy Family	http://harrypotter.warnerbros.com/harrypotterandthehalf-bloodprince/dvd/index.html	767	witch magic broom school of witchcraft wizardry	en	Harry Potter and the Half-Blood Prince	As Harry begins his sixth year at Hogwarts, he discovers an old book marked as 'Property of the Half-Blood Prince', and begins to learn more about Lord Voldemort's dark past.	98.885637	[{"name": "Warner Bros.", "id": 6194}, {"name": "Heyday Films", "id": 7364}]	[{"iso_3166_1": "GB", "name": "United Kingdom"}, {"iso_3166_1": "US", "name": "United States of America"}]	2009-07-07	933959197	153.0	[{"iso_639_1": "en", "name": "English"}]	Released	Dark Secrets Revealed	Harry Potter and the Half-Blood Prince	7.4	5293	Daniel Radcliffe Rupert Grint Emma Watson Tom Felton Michael Gambon	[{'name': 'Bruno Delbonnel', 'gender': 0, 'department': 'Camera', 'job': 'Director of Photography', 'credit_id': '52fe4273c3a36847f801fab1', 'id': 2423}, {'name': 'Stephanie McMillan', 'gender': 1, 'department': 'Art', 'job': 'Set Decoration', 'credit_id': '52fe4273c3a36847f801faf3', 'id': 5331}, {'name': 'Stuart Craig', 'gender': 2, 'department': 'Art', 'job': 'Production Design', 'credit_id': '52fe4273c3a36847f801fac3', 'id': 5491}, {'name': 'J.K. Rowling', 'gender': 1, 'department': 'Writing', 'job': 'Novel', 'credit_id': '52fe4273c3a36847f801fa8d', 'id': 10966}, {'name': 'Steve Kloves', 'gender': 2, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '52fe4273c3a36847f801fa87', 'id': 10967}, {'name': 'David Heyman', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4273c3a36847f801fa99', 'id': 10968}, {'name': 'Andrew Ackland-Snow', 'gender': 2, 'department': 'Art', 'job': 'Supervising Art Director', 'credit_id': '57090677c3a3681d3a0030ff', 'id': 10710}, {'name': 'Gary Tomkins', 'gender': 2, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '56a77c7ac3a36819d000365f', 'id': 11225}, {'name': 'Jany Temime', 'gender': 1, 'department': 'Costume & Make-Up', 'job': 'Costume Design', 'credit_id': '52fe4273c3a36847f801faf9', 'id': 11227}, {'name': 'Fiona Weir', 'gender': 1, 'department': 'Production', 'job': 'Casting', 'credit_id': '52fe4273c3a36847f801fabd', 'id': 11295}, {'name': 'Alastair Bullock', 'gender': 0, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '56a77cd192514129f500318d', 'id': 11296}, {'name': 'David Yates', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe4273c3a36847f801fa81', 'id': 11343}, {'name': 'Nicholas Hooper', 'gender': 2, 'department': 'Sound', 'job': 'Original Music Composer', 'credit_id': '56a77c58c3a36819de002ec8', 'id': 11344}, {'name': 'Mark Day', 'gender': 2, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe4273c3a36847f801fab7', 'id': 11345}, {'name': 'David Barron', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4273c3a36847f801fa93', 'id': 65614}, {'name': 'Tim Lewis', 'gender': 0, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4273c3a36847f801fa9f', 'id': 89320}, {'name': 'Lionel Wigram', 'gender': 0, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '52fe4273c3a36847f801faa5', 'id': 41289}, {'name': 'Molly Hughes', 'gender': 0, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '56a77d26c3a36819ce003335', 'id': 89383}, {'name': 'Tino Schaedler', 'gender': 0, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '56a77cb89251412a04003164', 'id': 89384}, {'name': 'Hattie Storey', 'gender': 0, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '56a77c9ec3a36819da003242', 'id': 89385}, {'name': "Sloane U'Ren", 'gender': 0, 'department': 'Art', 'job': 'Art Direction', 'credit_id': '56a77d0b92514129fb003270', 'id': 89386}, {'name': 'Anna Worley', 'gender': 1, 'department': 'Directing', 'job': 'Script Supervisor', 'credit_id': '56a77d80c3a36819cb003104', 'id': 1389548}, {'name': 'Jaap Buitendijk', 'gender': 0, 'department': 'Camera', 'job': 'Still Photographer', 'credit_id': '56a77f5092514129f100344b', 'id': 1393448}, {'name': 'Kate Baird', 'gender': 0, 'department': 'Editing', 'job': 'First Assistant Editor', 'credit_id': '56a77dddc3a36819da003271', 'id': 1408843}, {'name': 'Hermione Byrt', 'gender': 0, 'department': 'Editing', 'job': 'First Assistant Editor', 'credit_id': '56a77dc292514130e7000bc6', 'id': 1473175}, {'name': 'Richard Davies', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Assistant Costume Designer', 'credit_id': '595bf7d6c3a36825e8057170', 'id': 1551777}, {'name': 'Stuart Wilson', 'gender': 0, 'department': 'Sound', 'job': 'Production Sound Mixer', 'credit_id': '56a77e0c92514129ef003102', 'id': 1568519}]	David Yates
9	9	250000000	Action Adventure Fantasy	http://www.batmanvsupermandawnofjustice.com/	209112	dc comics vigilante superhero based on comic book revenge	en	Batman v Superman: Dawn of Justice	Fearing the actions of a god-like Super Hero left unchecked, Gotham City’s own formidable, forceful vigilante takes on Metropolis’s most revered, modern-day savior, while the world wrestles with what sort of hero it really needs. And with Batman and Superman at war with one another, a new threat quickly arises, putting mankind in greater danger than it’s ever known before.	155.790452	[{"name": "DC Comics", "id": 429}, {"name": "Atlas Entertainment", "id": 507}, {"name": "Warner Bros.", "id": 6194}, {"name": "DC Entertainment", "id": 9993}, {"name": "Cruel & Unusual Films", "id": 9995}, {"name": "RatPac-Dune Entertainment", "id": 41624}]	[{"iso_3166_1": "US", "name": "United States of America"}]	2016-03-23	873260194	151.0	[{"iso_639_1": "en", "name": "English"}]	Released	Justice or revenge	Batman v Superman: Dawn of Justice	5.7	7004	Ben Affleck Henry Cavill Gal Gadot Amy Adams Jesse Eisenberg	[{'name': 'Hans Zimmer', 'gender': 2, 'department': 'Sound', 'job': 'Original Music Composer', 'credit_id': '553bf23692514135c8002886', 'id': 947}, {'name': 'Charles Roven', 'gender': 0, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe4d5bc3a368484e1e4c2d', 'id': 282}, {'name': 'Christopher Nolan', 'gender': 2, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '553bf2ba925141125600a15d', 'id': 525}, {'name': 'Emma Thomas', 'gender': 1, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '553bf2cac3a3685cf8005eba', 'id': 556}, {'name': 'David S. 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	df_index	budget	genres	homepage	id	keywords	original_language	original_title	overview	popularity	production_companies	production_countries	release_date	revenue	runtime	spoken_languages	status	tagline	title	vote_average	vote_count	cast	crew	director
4793	4793	0	Drama	NaN	182291	confession hazing gang member latino lgbt	en	On The Downlow	Isaac and Angel are two young Latinos involved in a south side Chicago gang. They have a secret in a world where secrets are forbidden.	0.029757	[{"name": "Iconoclast Films", "id": 26677}]	[{"iso_3166_1": "US", "name": "United States of America"}]	2004-04-11	0	90.0	[]	Released	Two gangs. One secret. One crossroad.	On The Downlow	6.0	2	Tony Sancho Michael Cortez Donato Cruz Felipe Camacho Carmen Cenko	[{'name': 'Tadeo Garcia', 'gender': 0, 'department': 'Directing', 'job': 'Director', 'credit_id': '548c416392514122ef00197d', 'id': 1398500}, {'name': 'Tadeo Garcia', 'gender': 0, 'department': 'Writing', 'job': 'Story', 'credit_id': '548c419a92514122f2001830', 'id': 1398500}, {'name': 'Roger B. Domian', 'gender': 0, 'department': 'Writing', 'job': 'Screenplay', 'credit_id': '548c4176c3a36820ba0017f2', 'id': 1398501}, {'name': 'Roger B. Domian', 'gender': 0, 'department': 'Writing', 'job': 'Story', 'credit_id': '548c418792514122f9001a1e', 'id': 1398501}]	Tadeo Garcia
4794	4794	0	Thriller Horror Comedy	NaN	286939	NaN	en	Sanctuary: Quite a Conundrum	It should have been just a normal day of sex, fun, alcohol, hormones and debauchery for Tabitha and Mimi, two over-privileged twenty-somethings. But that so-called normalcy gets tossed out the window when a devastating event occurs at a pool party.	0.166513	[{"name": "Gold Lion Films", "id": 37870}, {"name": "T-Street Productions", "id": 37871}]	[{"iso_3166_1": "US", "name": "United States of America"}]	2012-01-20	0	82.0	[{"iso_639_1": "en", "name": "English"}]	Released	NaN	Sanctuary: Quite a Conundrum	0.0	0	Sasha Ramos Erin Cline Emily Rogers Anthony Rutowicz Joe Coffey	[{'name': 'Thomas L. Phillips', 'gender': 0, 'department': 'Directing', 'job': 'Director', 'credit_id': '545f8107c3a3686cbb0041fd', 'id': 1171387}, {'name': 'Thomas L. Phillips', 'gender': 0, 'department': 'Production', 'job': 'Producer', 'credit_id': '545f8126c3a3686cbb004202', 'id': 1171387}, {'name': 'Thomas L. Phillips', 'gender': 0, 'department': 'Writing', 'job': 'Writer', 'credit_id': '545f8111c3a3680b5d000812', 'id': 1171387}]	Thomas L. Phillips
4795	4795	0	Drama	NaN	124606	gang audition police fake homeless actress	en	Bang	A young woman in L.A. is having a bad day: she's evicted, an audition ends with a producer furious she won't trade sex for the part, and a policeman nabs her for something she didn't do, demanding fellatio to release her. She snaps, grabs his gun, takes his uniform, and leaves him cuffed to a tree where he's soon having a defenseless chat with a homeless man. She takes off on the cop's motorcycle and, for an afternoon, experiences a cop's life. She talks a young man out of suicide and then is plunged into violence after a friendly encounter with two "vatos." She is torn between self-protection and others' expectations. Is there any resolution for her torrent of feelings?	0.918116	[{"name": "Asylum Films", "id": 10571}, {"name": "FM Entertainment", "id": 26598}, {"name": "Eagle Eye Films Inc.", "id": 40739}]	[{"iso_3166_1": "US", "name": "United States of America"}]	1995-09-09	0	98.0	[{"iso_639_1": "en", "name": "English"}]	Released	Sometimes you've got to break the rules	Bang	6.0	1	Darling Narita Peter Greene Michael Newland Erik Schrody Michael Artura	[{'name': 'Ash Baron-Cohen', 'gender': 0, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe4ab0c3a368484e161add', 'id': 77465}, {'name': 'Ash Baron-Cohen', 'gender': 0, 'department': 'Writing', 'job': 'Writer', 'credit_id': '55a6c2fdc3a3682fff0002d7', 'id': 77465}, {'name': 'Daniel M. Berger', 'gender': 0, 'department': 'Production', 'job': 'Producer', 'credit_id': '55a6c30bc3a36830080002b6', 'id': 77469}, {'name': 'Ladd Vance', 'gender': 0, 'department': 'Production', 'job': 'Producer', 'credit_id': '55a6c316c3a3682ff4000349', 'id': 551516}, {'name': 'David Gasperik', 'gender': 2, 'department': 'Crew', 'job': 'Cinematography', 'credit_id': '55a6c3269251411e1b0002c9', 'id': 1108768}, {'name': 'Orlando Aguillen', 'gender': 0, 'department': 'Sound', 'job': 'Original Music Composer', 'credit_id': '55a6c334c3a36830080002b9', 'id': 1487597}]	Ash Baron-Cohen
4796	4796	7000	Science Fiction Drama Thriller	http://www.primermovie.com	14337	distrust garage identity crisis time travel time machine	en	Primer	Friends/fledgling entrepreneurs invent a device in their garage that reduces the apparent mass of any object placed inside it, but they accidentally discover that it has some highly unexpected capabilities -- ones that could enable them to do and to have seemingly anything they want. Taking advantage of this unique opportunity is the first challenge they face. Dealing with the consequences is the next.	23.307949	[{"name": "Thinkfilm", "id": 446}]	[{"iso_3166_1": "US", "name": "United States of America"}]	2004-10-08	424760	77.0	[{"iso_639_1": "en", "name": "English"}]	Released	What happens if it actually works?	Primer	6.9	658	Shane Carruth David Sullivan Casey Gooden Anand Upadhyaya Carrie Crawford	[{'name': 'Shane Carruth', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe45e79251416c75066791', 'id': 76624}, {'name': 'Shane Carruth', 'gender': 2, 'department': 'Editing', 'job': 'Editor', 'credit_id': '560a6cfcc3a368681f001dfe', 'id': 76624}, {'name': 'Shane Carruth', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe45e79251416c75066797', 'id': 76624}, {'name': 'Shane Carruth', 'gender': 2, 'department': 'Writing', 'job': 'Writer', 'credit_id': '52fe45e79251416c750667af', 'id': 76624}, {'name': 'Shane Carruth', 'gender': 2, 'department': 'Sound', 'job': 'Music', 'credit_id': '52fe45e79251416c7506679d', 'id': 76624}, {'name': 'Shane Carruth', 'gender': 2, 'department': 'Crew', 'job': 'Cinematography', 'credit_id': '560a6ba2c3a3686824001e85', 'id': 76624}]	Shane Carruth
4797	4797	0	Foreign Thriller	NaN	67238	NaN	en	Cavite	Adam, a security guard, travels from California to the Philippines, his native land, for his father's funeral. He arrives in Manila. As he waits, a phone rings in his backpack; he answers it, and a male voice tells him that his mother and sister are captives and will be killed if Adam doesn't cooperate. Over the next hour, the voice sends Adam by bus, taxi, motorized tricycle, and on foot through an urban landscape of busy streets, cramped apartments, a fetid squatters' camp, a bank, a cockfighting arena, and a church. Adam's conversations with the voice cover murder, Islam, jihad, rebellion in Mindanao, and his family. What is it Adam will be commanded to do?	0.022173	[]	[]	2005-03-12	0	80.0	[]	Released	NaN	Cavite	7.5	2	NaN	[{'name': 'Neill Dela Llana', 'gender': 0, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe475dc3a368484e0c319f', 'id': 1174437}, {'name': 'Ian Gamazon', 'gender': 0, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe475dc3a368484e0c31a5', 'id': 1174438}]	Neill Dela Llana
4798	4798	220000	Action Crime Thriller	NaN	9367	united states\u2013mexico barrier legs arms paper knife guitar case	es	El Mariachi	El Mariachi just wants to play his guitar and carry on the family tradition. Unfortunately, the town he tries to find work in has another visitor...a killer who carries his guns in a guitar case. The drug lord and his henchmen mistake El Mariachi for the killer, Azul, and chase him around town trying to kill him and get his guitar case.	14.269792	[{"name": "Columbia Pictures", "id": 5}]	[{"iso_3166_1": "MX", "name": "Mexico"}, {"iso_3166_1": "US", "name": "United States of America"}]	1992-09-04	2040920	81.0	[{"iso_639_1": "es", "name": "Espa\u00f1ol"}]	Released	He didn't come looking for trouble, but trouble came looking for him.	El Mariachi	6.6	238	Carlos Gallardo Jaime de Hoyos Peter Marquardt Reinol Martinez Ramiro Gomez	[{'name': 'Robert Rodriguez', 'gender': 0, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe44eec3a36847f80b280b', 'id': 2294}, {'name': 'Robert Rodriguez', 'gender': 0, 'department': 'Camera', 'job': 'Director of Photography', 'credit_id': '52fe44eec3a36847f80b2847', 'id': 2294}, {'name': 'Robert Rodriguez', 'gender': 0, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe44eec3a36847f80b284d', 'id': 2294}, {'name': 'Robert Rodriguez', 'gender': 0, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe44eec3a36847f80b281d', 'id': 2294}, {'name': 'Robert Rodriguez', 'gender': 0, 'department': 'Writing', 'job': 'Author', 'credit_id': '52fe44eec3a36847f80b2811', 'id': 2294}, {'name': 'Carlos Gallardo', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '52fe44eec3a36847f80b2817', 'id': 20498}, {'name': 'Eric Guthrie', 'gender': 0, 'department': 'Sound', 'job': 'Music', 'credit_id': '52fe44eec3a36847f80b2829', 'id': 57473}, {'name': 'Chris Knudson', 'gender': 0, 'department': 'Sound', 'job': 'Music', 'credit_id': '52fe44eec3a36847f80b282f', 'id': 57474}, {'name': '\\u00c1lvaro Rodr\\u00edguez', 'gender': 0, 'department': 'Sound', 'job': 'Music', 'credit_id': '52fe44eec3a36847f80b2835', 'id': 57475}, {'name': 'Cecilio Rodr\\u00edguez', 'gender': 0, 'department': 'Sound', 'job': 'Music', 'credit_id': '52fe44eec3a36847f80b283b', 'id': 57478}, {'name': 'Mark Trujillo', 'gender': 0, 'department': 'Sound', 'job': 'Music', 'credit_id': '52fe44eec3a36847f80b2841', 'id': 57479}]	Robert Rodriguez
4799	4799	9000	Comedy Romance	NaN	72766	NaN	en	Newlyweds	A newlywed couple's honeymoon is upended by the arrivals of their respective sisters.	0.642552	[]	[]	2011-12-26	0	85.0	[]	Released	A newlywed couple's honeymoon is upended by the arrivals of their respective sisters.	Newlyweds	5.9	5	Edward Burns Kerry Bish\u00e9 Marsha Dietlein Caitlin Fitzgerald Daniella Pineda	[{'name': 'Edward Burns', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe487dc3a368484e0fb013', 'id': 12833}, {'name': 'Edward Burns', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '584a9e89c3a368141101e3b6', 'id': 12833}, {'name': 'Edward Burns', 'gender': 2, 'department': 'Writing', 'job': 'Writer', 'credit_id': '52fe487dc3a368484e0fb019', 'id': 12833}, {'name': 'William Rexer', 'gender': 0, 'department': 'Production', 'job': 'Producer', 'credit_id': '584a9ead92514157fa00ccae', 'id': 1066767}, {'name': 'William Rexer', 'gender': 0, 'department': 'Crew', 'job': 'Cinematography', 'credit_id': '584a9ee792514119bc01e99c', 'id': 1066767}, {'name': 'P.T. Walkley', 'gender': 0, 'department': 'Sound', 'job': 'Music', 'credit_id': '584a9ed2c3a368141a0201c7', 'id': 1251352}, {'name': 'Janet Gaynor', 'gender': 0, 'department': 'Editing', 'job': 'Editor', 'credit_id': '584aa1ba92514119b301ecfa', 'id': 1552358}, {'name': 'Aaron Lubin', 'gender': 0, 'department': 'Production', 'job': 'Producer', 'credit_id': '584a9e9e92514119b301eb56', 'id': 1566006}]	Edward Burns
4800	4800	0	Comedy Drama Romance TV Movie	http://www.hallmarkchannel.com/signedsealeddelivered	231617	date love at first sight narration investigation team	en	Signed, Sealed, Delivered	"Signed, Sealed, Delivered" introduces a dedicated quartet of civil servants in the Dead Letter Office of the U.S. Postal System who transform themselves into an elite team of lost-mail detectives. Their determination to deliver the seemingly undeliverable takes them out of the post office into an unpredictable world where letters and packages from the past save lives, solve crimes, reunite old loves, and change futures by arriving late, but always miraculously on time.	1.444476	[{"name": "Front Street Pictures", "id": 3958}, {"name": "Muse Entertainment Enterprises", "id": 6438}]	[{"iso_3166_1": "US", "name": "United States of America"}]	2013-10-13	0	120.0	[{"iso_639_1": "en", "name": "English"}]	Released	NaN	Signed, Sealed, Delivered	7.0	6	Eric Mabius Kristin Booth Crystal Lowe Geoff Gustafson Benjamin Hollingsworth	[{'name': 'Carla Hetland', 'gender': 0, 'department': 'Costume & Make-Up', 'job': 'Costume Design', 'credit_id': '52fe4df3c3a36847f8275ecf', 'id': 23816}, {'name': 'Harvey Kahn', 'gender': 2, 'department': 'Production', 'job': 'Producer', 'credit_id': '583328efc3a368675d0016e4', 'id': 32733}, {'name': 'Adam Sliwinski', 'gender': 2, 'department': 'Camera', 'job': 'Director of Photography', 'credit_id': '52fe4df3c3a36847f8275eb7', 'id': 43925}, {'name': 'Martha Williamson', 'gender': 1, 'department': 'Writing', 'job': 'Writer', 'credit_id': '52fe4df3c3a36847f8275eb1', 'id': 166873}, {'name': 'Martha Williamson', 'gender': 1, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '58332c6ac3a3686753001dcf', 'id': 166873}, {'name': 'Joel S. Rice', 'gender': 2, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '554ea9ddc3a36879530001d9', 'id': 174065}, {'name': 'Jackie Lind', 'gender': 1, 'department': 'Production', 'job': 'Casting', 'credit_id': '5833288e92514103450018f0', 'id': 435006}, {'name': 'Shana Landsburg', 'gender': 0, 'department': 'Production', 'job': 'Casting', 'credit_id': '5833289ac3a36867500019b1', 'id': 551521}, {'name': 'Renee Read', 'gender': 1, 'department': 'Art', 'job': 'Production Design', 'credit_id': '52fe4df3c3a36847f8275ec9', 'id': 1012891}, {'name': 'Hal Beckett', 'gender': 2, 'department': 'Sound', 'job': 'Original Music Composer', 'credit_id': '52fe4df3c3a36847f8275ec3', 'id': 1099146}, {'name': 'Scott Smith', 'gender': 0, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe4df3c3a36847f8275eab', 'id': 1219158}, {'name': 'Scott Smith', 'gender': 0, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '58332c3f9251410348001bf2', 'id': 1219158}, {'name': 'Lisa Binkley', 'gender': 0, 'department': 'Editing', 'job': 'Editor', 'credit_id': '52fe4df3c3a36847f8275ebd', 'id': 1271268}]	Scott Smith
4801	4801	0	NaN	http://shanghaicalling.com/	126186	NaN	en	Shanghai Calling	When ambitious New York attorney Sam is sent to Shanghai on assignment, he immediately stumbles into a legal mess that could end his career. With the help of a beautiful relocation specialist, a well-connected old-timer, a clever journalist, and a street-smart legal assistant, Sam might just save his job, find romance, and learn to appreciate the beauty and wonders of Shanghai. Written by Anonymous (IMDB.com).	0.857008	[]	[{"iso_3166_1": "US", "name": "United States of America"}, {"iso_3166_1": "CN", "name": "China"}]	2012-05-03	0	98.0	[{"iso_639_1": "en", "name": "English"}]	Released	A New Yorker in Shanghai	Shanghai Calling	5.7	7	Daniel Henney Eliza Coupe Bill Paxton Alan Ruck Zhu Shimao	[{'name': 'Daniel Hsia', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe4ad9c3a368484e16a36b', 'id': 208138}, {'name': 'Daniel Hsia', 'gender': 2, 'department': 'Writing', 'job': 'Writer', 'credit_id': '52fe4ad9c3a368484e16a371', 'id': 208138}]	Daniel Hsia
4802	4802	0	Documentary	NaN	25975	obsession camcorder crush dream girl	en	My Date with Drew	Ever since the second grade when he first saw her in E.T. The Extraterrestrial, Brian Herzlinger has had a crush on Drew Barrymore. Now, 20 years later he's decided to try to fulfill his lifelong dream by asking her for a date. There's one small problem: She's Drew Barrymore and he's, well, Brian Herzlinger, a broke 27-year-old aspiring filmmaker from New Jersey.	1.929883	[{"name": "rusty bear entertainment", "id": 87986}, {"name": "lucky crow films", "id": 87987}]	[{"iso_3166_1": "US", "name": "United States of America"}]	2005-08-05	0	90.0	[{"iso_639_1": "en", "name": "English"}]	Released	NaN	My Date with Drew	6.3	16	Drew Barrymore Brian Herzlinger Corey Feldman Eric Roberts Griffin Dunne	[{'name': 'Clark Peterson', 'gender': 2, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '58ce021b9251415a390165d9', 'id': 6888}, {'name': 'Andrew Reimer', 'gender': 2, 'department': 'Production', 'job': 'Executive Producer', 'credit_id': '58ce0232c3a36850e90157da', 'id': 61051}, {'name': 'Brian Herzlinger', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe44e8c3a368484e03da8d', 'id': 85563}, {'name': 'Jon Gunn', 'gender': 2, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe44e8c3a368484e03da87', 'id': 94471}, {'name': 'Brett Winn', 'gender': 0, 'department': 'Directing', 'job': 'Director', 'credit_id': '52fe44e8c3a368484e03da97', 'id': 997560}]	Brian Herzlinger

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